Relevant social searching and user centric data analysis via user and peer group parameters via a dynamic interface

ABSTRACT

A system and method that enables the user to search and identify meaningful and relevant information, based upon the weighted, custom parameters provided by the user and parameters or rules defined by the community of users as a group, with the option of utilizing user profile information to tune or detune searching, comparing or contrasting, and predicting. User profile information is collected and organized with data and feedback collected from other users. The results are then tailored to a weighted, cumulative summary result, for display that benefits the contributing user and subsequent future community or user group associations (UGA). The methods provide a summary, or result, that can be tailored specifically to the user based upon weighted rules (algorithms) and parameters defined by the user (or a user group as a whole), and the weighted rules and parameters defined as meaningful by the user (group).

CROSS-REFERENCE TO RELATED APPLICATIONS

This patent application Ser. No. 13/848,715, is a divisional of U.S.patent application Ser. Nos. 13/453,990 and 11/964,703 entitled“USER-CENTRIC, USER-WEIGHTED METHOD AND APPARATUS FOR IMPROVINGRELEVANCE AND ANALYSIS OF INFORMATION SHARING AND SEARCHING” filed onDec. 26, 2007 (which issued as U.S. Pat. No. 8,166,026 on Apr. 24,2012), which claims benefit to U.S. Provisional Patent Application No.60/877,047 filed on Dec. 26, 2006, each of which is hereby incorporatedby reference in its entirety for all purposes.

FIELD OF THE INVENTION

This invention relates to computerized methods and apparatus forsearching, analyzing, and presenting data, and more particularly topersonalizing meaningful and relevant data using a user-defined,user-weighted, and a user-profile-driven method to obtain relevant dataand feedback tuning for searching, comparing, and analyzing historical,current, and predicting future momentum data.

BACKGROUND OF THE INVENTION

Conventional systems may define relevancy as the number of hits, thenumber of checkouts and other past and behavioral information gatheredfor user activity. In some instances, a simple input, or score, from theuser is collected and summarized as a number or another set of symbolslike ‘stars’. However, for most people, this type of scoring, orrelevancy, of the inquiry or search result lacks the specificinformation that would most benefit the user. To complicate the issuefurther, finding relevant information has become increasing moredifficult with the sheer volume of information now available on theinternet combined with the information being made available on a dailybasis on companies' intranet and other systems.

Several traditional, known approaches have been employed in an attemptto improve the relevancy of user input opinions or other data. Oneapproach comprises devising mechanisms to map a user's query to documentand concept-based query expansion, while another approach identifieseach concept and is expanded to a disjunctive set or group of conceptson the basis of relationships identified by the user. Another known ideais proposed in, “Incremental Relevance Feedback for InformationFiltering”, by J. Allen, Center for Intelligent Information RetrievalDept. of Computer Science, Univ. of Mass., Amherst, Mass. This conceptrelates to feedback techniques that factors in shifts of the userinterest patterns over a period of time.

Various publications provide certain aspects used in some embodiments ofthe present invention. These include:

-   -   “Incremental Relevance Feedback for Information Filtering”,        by J. Allan, Center for Intelligent Information Retrieval Dept.        of Computer Science, University of Massachusetts, Amherst, Mass.    -   “Using faces to represent points in k-dimensional space        graphically”, Herman Chernoff (1973), Journal of the American        Statistical Association 68 (342): 361-368.

U.S. PATENT PUBLICATION NUMBER 2006/0235860 A1 (which issued as U.S.Pat. No. 7,596,558 on Sep. 29, 2009), by BRETT BREWER, TITLED “SYSTEMAND METHOD FOR OBTAINING USER FEEDBACK FOR RELEVANCE TUNING” is herebyincorporated by reference. It describes a system and method forfacilitating user feedback pertaining to search results produced by asearch system in response to an input user query. The system may includean edit mode activation option provided in conjunction with the searchresults. The system may additionally include result manipulation toolstriggered in response to a user selection of the edit mode activationoption, the result manipulation tools allowing the user to manipulatethe search results. The result manipulation tools may include a sortinginterface for allowing a user to sort search results. The system mayfurther include a feedback receiving mechanism for receiving and storingthe user-manipulated search results for future ranking input or searchresult personalization input. In some embodiments; the sorting interfaceallows the user to drag and drop results in the selected descendingorder. Some embodiments further include providing a re-orderinginterface including drag and drop capability that allows the user tore-order the search results in descending order based on relevance.

U.S. PATENT PUBLICATION NUMBER 2006/0112099 A1 (which issued as U.S.Pat. No. 7,698,279 on Apr. 13, 2010), by TIMOTHY MUSGROVE, PRODUCTFEATURE AND RELATION COMPARISON SYSTEM is hereby incorporated byreference. It describes a method of presenting data regarding products.Feature categories are assigned to each product category based onavailable data. A weighted importance is assigned to each featurecategory of each product category based on the available data. The itemsin the product category are ranked according to the weighted importanceof the feature categories of each item, and the evaluation metrics ofeach feature category.

U.S. Pat. No. 6,256,633, to SHANDA DHARAP, “CONTEXT BASED AND USERPROFILE DRIVEN INFORMATION RETRIEVAL” is hereby incorporated byreference. It describes that a user is enabled to navigate through anelectronic data base in a personalized manner. A context is createdbased on a profile of the user, the profile being at least partly formedin advance. Candidate data is selected from the data base under controlof the context and the user is enabled to interact with the candidates.The profile is based on topical information supplied by the user inadvance and a history of previous accesses from the user to the database.

U.S. Pat. No. 7,089,237, to DONALD TURNBULL, “INTERFACE AND SYSTEM FORPROVIDING PERSISTENT CONTEXTUAL RELEVANCE FOR COMMERCE ACTIVITIES IN ANETWORKED ENVIRONMENT” is hereby incorporated by reference. It describesa search and recommendation system that employs the preferences andprofiles of individual users and groups within a community of users, aswell as information derived from categorically organized contentpointers, to augment electronic commerce related searches, re-ranksearch results, and provide recommendations for commerce related objectsbased on an initial subject-matter query and an interaction history of auser. The search and recommendation system operates in the context of acontent pointer manager, which stores individual users' content pointers(some of which may be published or shared for group use) on acentralized content pointer database connected to a network. The sharedcontent pointer manager is implemented as a distributed program,portions of which operate on users' terminals and other portions ofwhich operate on the centralized content pointer database. A user'scontent pointers are organized in accordance with a local topicalcategorical hierarchy. The hierarchical organization is used to define arelevance context within which returned objects are evaluated andordered.

U.S. PATENT PUBLICATION NUMBER 2006/0101017 A1 (which issued as U.S.Pat. No. 7,426,499 on Sep. 16, 2008), by JEFFREY EDER, “SEARCH RANKINGSYSTEM” is hereby incorporated by reference. It describes acomputer-based media, method and system for prioritizing search resultsfor an individual, a group, a team, a division, an organization or somecombination thereof.

U.S. Pat. No. 7,096,214, to KRISHNA BHARAT, “SYSTEM AND METHOD FORSUPPORTING EDITORIAL OPINION IN THE RANKING OF SEARCH RESULTS” is herebyincorporated by reference. It describes a server that improves theranking of search results. The server includes a processor and a memorythat stores instructions and a group of query themes. The processorreceives a search query containing at least one search term, retrievesone or more objects based on the at least one search term and determineswhether the search query corresponds to at least one of the group ofquery themes. The processor then ranks the one or more objects based onwhether the search query corresponds to at least one of the group ofquery themes and provides the ranked one or more objects to a user.

U.S. Pat. No. 7,031,961, to JAMES PITKOW, “SYSTEM AND METHOD FORSEARCHING AND RECOMMENDING OBJECTS FROM A CATEGORICALLY ORGANIZEDINFORMATION REPOSITORY” is hereby incorporated by reference. Itdescribes a search and recommendation system employs the preferences andprofiles of individual users and groups within a community of users, aswell as information derived from categorically organized contentpointers, to augment Internet searches, re-rank search results, andprovide recommendations for objects based on an initial subject-matterquery. The search and recommendation system operates in the context of acontent pointer manager, which stores individual users' content pointers(some of which may be published or shared for group use) on acentralized content pointer database connected to the Internet. Theshared content pointer manager is implemented as a distributed program,portions of which operate on users' terminals and other portions ofwhich operate on the centralized content pointer database. A user'scontent pointers are organized in accordance with a local topicalcategorical hierarchy. The hierarchical organization is used to define arelevance context within which returned objects are evaluated andordered.

U.S. PATENT PUBLICATION NUMBER 2006/0218146, ELAN BITAN, “INTERACTIVEUSER CONTROLLED RELEVANCE RANKING INFORMATION IN AN INFORMATION SEARCHSYSTEM” is hereby incorporated by reference. It describes an apparatusand system for providing an ability to conduct a secondary search usingresults provided by a first search capability. This secondary search isintegrated with the first search and functions as an added tool oraccessory. The present invention allows for user control of searchranking, search viewing and search presentations thus affording morerelevant information retrieval. Searchers can dynamically andinteractively examine and manipulate the search results to improverelevance and quickly satisfy their search objectives.

U.S. PATENT PUBLICATION NUMBER 2006/0206505 (which issued as U.S. Pat.No. 7,680,855 on Mar. 16, 2010), by ADAM HYDER, “SYSTEM AND METHOD FORMANAGING LISTINGS” is hereby incorporated by reference. It describes acomputer system and method for capture, managing and presenting dataobtained from various often unrelated postings via the Internet forexamination by a user. This system includes a scraping module having oneor more scraping engines operable to scrape information data sets fromlistings on the corporate sites and web sites, direct feeds, and othersources, wherein the scraping module receives and stores the scrapedlisting information data sets in a database. The system also has amanagement platform coordinating all operation of and communicationbetween the sources, system administrators and processing modules. Theprocessing modules in the platform include scraping management moduleanalyzing selected scraped data stored in the database, and acategorization module that examines and categorizes each data set storedin the database into one or more of a predetermined set of categoriesand returns categorized data sets to the database.

U.S. Pat. No. 6,904,455, to ROBERT YEN, “METHOD AND SYSTEM FOR PROVIDINGLOCAL CONTENT FOR USE IN PARTIALLY SATISFYING INTERNET DATA REQUESTSFROM REMOTE SERVERS” is hereby incorporated by reference. It describesimproved techniques for data delivery from a server machine to clientmachines through a network. The techniques reduce the demands onconnection bandwidth between the client machines and the network, andthus enable media-rich data to be delivered with reduced amounts ofnetwork bandwidth. The techniques also reduce the bandwidth demands onnetwork servers and overall network infrastructure.

Other background for the present invention can be found in U.S. Pat. No.6,256,633 “CONTEXT-BASED AND USER-PROFILE DRIVEN INFORMATION RETRIEVAL,”and U.S. Pat. No. 6,735,568 “METHOD AND SYSTEM FOR IDENTIFYING PEOPLEWHO ARE LIKELY TO HAVE A SUCCESSFUL RELATIONSHIP,” which are herebyincorporated by reference.

What is needed is an improved method and apparatus to increase therelevancy of search results and to allow improved analysis of data thatis collected.

SUMMARY OF THE INVENTION

In some embodiments, the present invention provides a computerizedmethod and apparatus for searching, analyzing, and presenting data, andmore particularly to personalizing meaningful and relevant data using auser-defined, user-weighted, and a user-profile-driven method to obtainrelevant data and feedback tuning for searching, comparing, andanalyzing historical, current, and predicting future momentum data. Someembodiments further include enabling user-centric meaningful andrelevant information in the form of input data or feedback. Someembodiments enable and facilitate sharing of data and user defined anduser weighted feedback and decisions with regards to purchasing,evaluating, comparing, predicting, searching and browsing a particularproduct, service, individual event or other user-defined topic. Someembodiments define the methods of eliciting, collecting, organizing,processing, weighting and retrieving meaningful and relevant contentprovided by the input of individual weighted and group weightedparameters for the benefit of subsequent users and groups of users as ashared community.

The invention improves upon shared environments such as HypertextTransport Protocol (“http”) and directory indexing or ‘bookmarking’, tobenefit clients who desire to obtain meaningful user input data (orfeedback) from other users by providing a tailored search result. Inaddition to incorporating user profile information, the method includesadding user (and user group) defined parameters, rules (algorithms) ormetrics and feedback that, in some embodiment, involve weighted criteriaor parameters provided by the user. Data gathered (in one embodimentreferred to as the uAffect input) is then weighted and configured bycriteria and/or parameters provided by the community of users as a groupwith user profile information factored into the results, based upon userdefinitions, rules, parameters and ‘use’ or utility context. Resultsthen display a cumulative, weighted and tailored result to the user anduser group as a whole (in one embodiment referred to as the uEffectoutput). In some embodiments, this invention can be used to track dataabout topics, businesses, products and other information to determinetrending, prediction and historical analysis of the topic, person,event, business, product, or service. The user-defined anduser-contributed data can be organized as such to determine and trackthe momentum quotient.

This invention provides a system and method that enables the user tosearch and identify meaningful and relevant information, based upon theweighted, custom parameters provided by the user and parameters or rulesdefined by the community of users as a group, with the option ofutilizing user profile information to tune or detune searching,comparing or contrasting, and predicting. User profile information iscollected and organized with data and feedback collected from otherusers. The results are then tailored to a weighted, cumulative summaryresult, for display that benefits the contributing user and subsequentfuture community or user group associations (UGAs). The methods providea summary, or result, that can be tailored specifically to the userbased upon weighted rules (algorithms) and parameters defined by theuser (or a user group as a whole), and the weighted rules and parametersdefined as meaningful by the user (group). The resulting cumulative andweighted results provide more meaningful and relevant data. User inputdata and summary results are displayed, in some embodiments, in adynamic, linked, multivariate symbol, graph or figure for ready accessvia computer or mobile device.

Capturing the data within the system and method of this invention,relevant and specific data can be collected, analyzed and tailored thesearching user. The user contributing data and feedback will belongtypically to more then one user group or association, for example, auser may belong to the ‘over 40 years old’ association, and also belongto the ‘professional photographer’ and the ‘amateur guitar player’associations. When analyzing or searching for feedback, the searchingquery can weight certain parameters optimizing the search, and alsoinclude or exclude feedback from certain associations further tuning thesearch result generating a more meaningful and relevant result. Forstatistical modeling, this can be used to analyze historical trends,determine and predict future trends and to define and determine themomentum quotient of the topic, product or other subject from thepriorities, weighting, and perspectives of defined associations or usergroups.

In general terms, meaningful and relevant information for usersattempting to search, compare, analyze and predict trends of data isbest obtained from information provided by other users, potentially byusers with similar profiles and ‘use’ of data context. In mostinstances, the concept of viewing pulled or ‘demanded’ data, feedback orinformation (relevancy determined by the users, a user group, communityor a peer group) as opposed to viewing pushed or ‘supplied’ data orfeedback (provided by the promoters, authors of information and othercontent providers or search engines) is considered more meaningful andrelevant for the users as a whole.

Key components to effective information and data search, analysis andretrieval lies in enabling the individual users, in conjunction with theuser groups, to configure the user centric, user defined and userweighted parameters, rules (algorithms), factors, ‘use’ of data context,tools and mechanisms. This unique approach optimizes searching,comparing or contrasting, analyzing, and predicting trends, markets,behaviors and other information gathered from a user defined criteria oforganizing the data. One of the unique aspects of this invention is thatit allows the users to determine the parameters or factors that areimportant to them as individuals, and define the parameters and factorsimportant to the user community or group as a whole, and then weight therelevance of all factors and parameters to be considered in thefeedback, scores or other data. Searching, comparing or analyzing datawithin a dashboard application provides the user with the ability todefine and prioritize the topics and parameters important to the searchquery. Cumulative results provide meaningful and relevant feedback andare displayed in a weighted, cumulative result in a meaningful summaryof the data set or symbol with multiple variables indicated within thedisplayed symbol. The symbols, in some embodiments, are dynamicallylinked to display, elicit, and receive information.

The present system and method maintains a centralized database ofmeaningful data pertaining to users. Information that is gathered andinformation that is provided by the user beyond ‘scores’ or ‘ratings’include, in some embodiments; the individual profile information of theuser, individual meaningful feedback (regarding a person, product,service or event), the weighted parameters, weighted factors and rulesin which to categorize and prioritize the information provided, stored,displayed and analyzed. Using the system that provides and hosts asharing and communication platform, the user can also have the option ofproviding meaningful information to the community group, or associationas a whole including the categorizing and prioritizing the relevantparameters, scores and rules about a topic for defining more meaningfuland relevant information (or feedback).

In maintaining a centralized database, the system has the ability ofharnessing user-centric data to organize and manage the inputinformation collected by the users (in some embodiments to include theindividual user profile information, implicit, explicit, implied data toinclude user feedback on various topics and user input including ratingsor scores and other information, on each of the group or communityparameters that reference each topic). Data is available in the presentinvention as an integrated data input and feedback interface. Thisapparatus allows for several operations to be performed, includingenhanced meaningful data search and retrieval, enhanced meaningfulresults, data analysis and data predictability outputs and summaries.Manipulated data search results, according to user and UGA definitions,are stored for additional analysis by a ranking system. Outputs aredisplayed and made available to the users in a predefined format orsymbol defined by the user, or the UGA as a whole.

The method herein in one embodiment includes a dashboard for thefunctions of searching, comparing, collecting and analyzing data. Thedashboard (see FIG. 7 and PDA figure) are fully integrated, real-timeuser interface(s) with edit functions that can utilize several tools,defined and weighted by the user, to manipulate and optimize thefunctions described above and other customized functions defined by theuser or the user group. The dashboard or other input apparatus enablesthe user to easily switch from a standard search function to the userdefined and weighted search function. The apparatus has the ability todisplay multivariate results that can graphically represent severalvariables, factors, scores, rankings and parameters. The results can bedisplayed by the display and notification preferences defined by thesearching user or the parameters recommended by a collective user group,community or association.

Analyzing trends or tuning of the heuristics and algorithms, includesevaluating the topics and weighted parameters defined by the user andcommunities, combined with user profile information and the feedback andscoring data gathered over time. The system benefits users by providingpowerful trending and prediction analysis when economic models andstatistical tools are employed for modeling tools and techniquesincluding momentum analysis. To enhance the relevancy of search or dataanalysis, a user can search parameters and profiles from the perspectiveof a UGA that the searcher may or may not directly belong to.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a system overview illustrating remote users accessing thedatabase.

FIG. 2 is an illustration of one embodiment of the system where a usercontributes data and can view the cumulative summary result. FIG. 2.1outlines another embodiment of the invention.

FIG. 3 is an illustration of one embodiment of the system and inventionand the database supporting the system.

FIG. 4 is an illustration of one embodiment wherein the user, with anaccess of Level B, inputs data contributing to a (uAffect) Experienceand Contributing to uEffect result. FIG. 4.1 outlines another embodimentof the invention.

FIG. 5, is an illustration of one embodiment wherein the Usercontributes to the uEffect score and parameter weightings.

FIG. 6 is an illustration of one embodiment wherein the User VolunteersProfile Information for the Benefit of Obtaining a uEffectResult/Score/Symbol Tailored and Weighted with Other Users With SimilarProfiles/Interests/Associations for Purposes of Social Networking andGathering, Feedback Sharing, and Prediction and Notification of FutureProducts, Services and Behaviors.

FIG. 7 is an illustration of one embodiment wherein the user utilizes adash board to search, compare and analyze data via the user group's andthe user's weighted parameters.

FIG. 8 is an illustration of one embodiment wherein the user utilizes adash board to compare products that the system recommends based uponweighted relevant search parameters defined by the user.

FIG. 9 is an illustration of one embodiment that demonstrates momentumtrend analysis (MTA).

FIG. 10 is an illustration of one embodiment wherein the individualuser's weightings, parameters, filters, tunings, and other searchcriteria are grouped into user group associations (UGA).

FIG. 11 is an illustration of one embodiment wherein a user accesses thesystem via a personal communication device to access summary results ofsuggested and searched movies via user defined parameters and searchcriteria.

FIG. 12 is an illustration of one embodiment of a data collection andanalysis of user parameters generating a summary symbol.

FIG. 13 is an illustration of one embodiment illustrating momentumtrends, a three dimensional display of the results in differentquadrants, and various elements of user group associations (UGA).

FIG. 14 is a flow chart of one embodiment and a chart of classifying andordering collected data.

FIG. 15 is an example of one embodiment of the system.

FIG. 16 is an example of one embodiment of the system wherein the useraccesses the system.

FIG. 17 is an example of one embodiment of the network system overview.

FIG. 18 is one embodiment of a first time user, topic feedback set-up ofthe system network (e.g., Internet).

FIG. 19 is one embodiment of an initial user set-up of a user groupassociation.

FIG. 20 is one embodiment of generating a summary symbol (SS).

FIG. 21 is one embodiment of a system framework.

FIG. 22 is one embodiment of a user adding a new parameter.

FIG. 23 is one embodiment wherein the user has interaction with thesystem contributing to data input and feedback.

FIG. 24 is one embodiment wherein the user modifies and adds (or“suggests”) a search parameter.

FIG. 25 illustrates two embodiments in formulas.

FIG. 26 illustrates two embodiments in formulas.

DESCRIPTION OF THE INVENTION I. System Overview

Although the following detailed description contains many specifics forthe purpose of illustration, a person of ordinary skill in the art willappreciate that many variations and alterations to the following detailsare within the scope of the invention. Accordingly, the followingpreferred embodiments of the invention are set forth without any loss ofgenerality to, and without imposing limitations upon the claimedinvention.

In the following detailed description of the preferred embodiments,reference is made to the accompanying drawings that form a part hereof,and in which are shown by way of illustration specific embodiments inwhich the invention may be practiced. It is understood that otherembodiments may be utilized and structural changes may be made withoutdeparting from the scope of the present invention.

The leading digit(s) of reference numbers appearing in the Figuresgenerally corresponds to the Figure number in which that component isfirst introduced, such that the same reference number is used throughoutto refer to an identical component which appears in multiple Figures.Signals and connections may be referred to by the same reference numberor label, and the actual meaning will be clear from its use in thecontext of the description.

Currently there is a disconnect in acquiring the meaningful and relevantinformation from stored data resources and utilizing the internet orother communication network, such a as cell phones, to collect therelevant feedback about specific topics from other users or groups ofusers. Beyond the large amount of general information and feedback,people are interested in acquiring relevant information and feedbackabout certain topics or subjects, (such as movies, theater, restaurantreviews, political information, products, services, events, people,hobbies and other topics) that is deemed relevant by the searching user.Currently, content that relates to determining relevant information isdelivered via the internet (including websites, blogs, video and audiostreaming and more) as well as offline sources (some examples beingtheater critics, movie critics, radio personalities, newspaper editorsand other staff). What is lacking is an organized, user-centric systemand method that delivers relevant information to the user and usercommunities wherein the users themselves define the weightings,parameters and factors that determine meaningful feedback information.

To further enhance the relevancy of the user input, the users need anapparatus and environment where they determine the weighting and thepriority of the relevant parameters and factors that define the feedbackmatrix for the individual user and the user group and topic as a whole.Obviously in some embodiments, media content aggregators such as searchengines provide a wealth of information regarding certain topics thatprovide user feedback in the form of search results. Yahoo, Google, AltaVista and IBM's CLEVER utilize several tools to “crawl” the web, comparedocuments, key-word searches, pattern matching analysis, number oflinks, page content searches, past user behavior and other collecteddata and other tools to monitor the behavior of users to help determinerelevance. Searches results are typically limited in usefulness becausethe results do not reflect the user's weighted preferences and oftengenerate an overwhelming number of results. Search results often areskewed to the ranking algorithms defined by the author, provider orcontent aggregator sometimes for the benefit of an advertiser or otherinfluential person or media concern that have defined the searchparameters.

Complicating matters, the accessibility of the internet has enabledmillions of people to access and post information online. This is anopportunity to access relevant content, however, the advantages of theinternet are not yet fully realized because of several reasons. Twopertinent reasons are: the sheer amount of information and searchresults available online oftentimes is overwhelming and too difficult todiscern meaningful information. Relevant content is not easily accessed,and the content source is at times unknown. Trying to determine relevantinformation is distorted by the person or entity that posts content.Accordingly, there is a need for a system that more completely searches,obtains and organizes information from a user-centric platform. Tooptimize this platform, the invention provides the database, system,method and apparatus to easily and efficiently combine the results fromgeneral search functions (for comparing and analyzing) from currentsources like Google, Yahoo and MSN, with search functions from thesystem using custom tailored parameters, combined with user profile andfeedback data obtained from other sources of input data over thecommunications network (cell phones, RFID, online and offline sources).

An apparatus and method are provided for eliciting and facilitating usergenerated data (in some embodiments to include user profile information,feedback, scores, ratings, weightings, search parameters, timing, ‘use’of data context and, or other meaningful data defined as useful by theuser and/or the user groups, communities, or associations). The systemprovides the method, apparatus and mechanism in which the data iselicited, collected, stored, and retrieved via a communications network.The system is designed to work independently, or in cooperation andcollaboration, with other data content aggregators and providers, searchengines, or media outlets.

FIG. 1 is an illustration that outlines one such embodiment of theinvention. Users can access the internet, intranet or othercommunications network 120, using various means from a computer or othernetworking device 110, a mobile consumer electronic device 111 or othermobile phone device 112. The system database 100, will be included inthe network. Some users who are seeking to access system data can do soin a variety of embodiments including a remote access 130, inconjunction with a browser 131, and a dashboard for input and display ofoutput information 132. In another example, a user 140, can customize adashboard 141 that works with a remote client 142, with storage for theapplication 143. Other users 150 can access data through a dashboard151, or other type of mobile device optimized to connect to the network160.

FIG. 2 outlines one embodiment of the invention. FIG. 2.1 outlinesanother embodiment of the invention where a user 201, can input data orfeedback, in this example referred to as a uAffect input, contributingto the overall summary result of a particular topic, in this examplereferred to as a uEffect result. A user can access a search result listof websites or blogs from a search engine 200. Searches typically referto a topic 210, and result in a list of search-recommended blogs 211,that incorporate the search query. By clicking on a link, the user canaccess the content of the blog or website 220. To provide feedback andscoring data, the user can access a uAffect link, in this example, alink at the bottom of the blog #1 page 221.

FIG. 2.1 outlines the parameter/value user input menu 230, is a datainput page that collects various scores 231, votes 232, user profileinformation and user input data 233. This information is collected,managed, organized and stored in system database that accessible over anetwork connection 300 (see FIG. 3). Referring again to FIG. 2.1, theinformation is organized by the topics, parameters and factors 240, andthe cumulative, weighted results 241. The results 242, 243, and 244 arethen computed to obtain a resulting uEffect score 245. The resultingscore can be a symbol or a combination of symbols, numbers, letters,visual effects, audio effects and other digits to convey multiplevariables is a concise, summary form.

Further referring to FIG. 2.1, the resulting uEffect symbol 245, can bethen displayed on the system or in a remote environment, at times in alist format 246.

FIG. 3 shows one embodiment of the system and method described hereinincorporates in one example what is referred to as a Platform ofAdvanced Meaningful Content (PAMC) that incorporates a software platformfor managing relevant feedback tools for any kind of content data FIG.3. An example of data may include (but not limited to) product, art,movie and creative content reviews, service feedback, event feedback(shows, campaigns), consumer and business feedback, educational andgovernment (politics) reviews, media articles, blogs, websites, etc. Thesystem is fully distributable among several machines and is scalable foraccess of both online and offline content and users. In some embodimentsa remote client and database are hosted on a remote mobile phone,computer or other device. Each module described below within thesoftware system is scalable and may include multiple instances dictatedby the amount of data to be handled and processed therein.

One embodiment of the system, referencing FIG. 3, for implementing theinvention, includes a general purpose computing device with processingunits and system buses that couples various system components includingthe system memory and database. Typical computer storage media in theform of volatile and/or nonvolatile memory and databases with randomaccess memory (RAM) coupled with a basic input/output system (BIOS) andrandom access memory (RAM). Data is stored in this example in a harddrive but other embodiments may include storage devices such asremovable media, remotely via the communications network to otherstorage devices including handheld user's devices. The computer in thisinvention operates in a networked environment using logical connectionsto one or more remote computers or other input/output devices.

The embodiment of the PAMC 300, in this illustration in FIG. 3, thesystem described is a computer software system for managing thecollection, processing and distribution of generated feedbackinformation provided by users and the user profiles of those accessingthe database(s). The System allows for a data capture from a pluralityof sources such as the internet 99, for compilation into a searchableand easily obtained data structure for meaningful and relevantinformation. The System includes an administrative portal module 310,providing system administration and operation control via a networkinterface accessing the data content manager. The administrative moduleincludes the various administration functions of access control. Themaster task scheduler and manager 320, provides the security and thegateway in which data is acquired and accessed.

The Data Input and Source Manager module 330, is the embodiment of anexemplary system operating through the use of any available means ofaccessing feedback content data including direct feeds, web based feeds,XML feeds, mobile and telephony feeds. The module is functionalitydescribed is applicable to any distributed information environmentwhereby information can be obtained by manual or automated systems.

The Rule Base and Quality Engine (RBQE) 340, compiles the data from theInput Source and processes the data based upon predefined parameters fordata storage in the database. Applying the rules set for the varioussources of data, the RBQE checks the accuracy of the input data andprepares the data for storage.

The Business Rules and Data Processing Manager 350, provides the gatewayin which the feedback profiles are administered and displayed remotely,via internet or server, to various search systems and sites.

The Data Output, Content and Symbol Engine 360, enables access to thestored database feedback and other content, and applies thepredetermined rules set to display the results of the data in raw formand symbolic, abbreviated form.

The User Profile Manager 370, provides the log in, authentication andvalidation process for the user community and the administrativecommunity. User data (volunteered information) is organized and storedin the database of User Profiles. The user data can be accessed bypermission and can be combined when providing feedback information tovarious interested parties. The PAMC profile manager works inconjunction with the PAMC Task Master Scheduler and the Business Rulesand Data Processing manager to; retrieve, display, search, compare,analyze queries. The system will alert users who have requestednotification options based upon predefined parameters that the user hasprovided.

The PAMC database(s) 380, illustrates one embodiment of the storage ofthe information. The staging database collects the incoming raw data,the cleansed and categorized database stores the input data in theorganized fashion determined by the processing managers. The userprofile information managed by the profile manager and stored in theuser profile and stored parameters, weightings and values.

Although many other internal and external components, applications,configurations and methods are not shown, those of ordinary skill in theart will appreciate that such components, applications and methods candeployed in a plurality of configurations.

The invention is described in the general context of computer executableinstructions. This invention may be implemented with other computer orcommunication system configurations, including but not inclusive ofhand-held devices, microprocessor-based or programmable consumerelectronics or other devices. The system may also be implemented in adistributed networked environment where tasks are performed by remoteprocessing devices that are linked through a network via the internet,intranet or other communications network. The program modules may belocated in both local and remote computer storage media including memorystorage devices.

FIG. 4 shows an embodiment, illustrating a user accessing the systemdata 400. The user is not required to provide any information. Referringnow to FIG. 4.1, for this illustration, we can define this method asuser access: level 1. The user in this example 401, who has a searchquery inquiring about new video games 402, may view the third partysearch engine results 403, (or in other embodiments results fromgenerated directly or in conjunction with the system). In this example,a uEffect resulting symbol or score generated by the PAMC 300 isdisplayed 404. The output compilation and weighted results that generatethe values displayed 404, can be viewed by clicking on the symbol 404 todisplay the resulting eEffect symbol parameters. The output compilationpage 405, will list the individual factors or parameters and results406, 407, 408, which define the resulting symbol or score 404.

For this example, because the user has not contributed profile and otherinformation, the resulting score doesn't reflect any personal profileinformation of the searching user. Nor does this level of system accessallow for tailored uEffect results wherein the user can weigh andprioritize the parameters that are meaningful and relevant to the user.

FIG. 5, is an illustration of one embodiment wherein the Usercontributes to the uEffect score and parameter weightings. By clickingon Game #1 (510) the user can access the content of the blog, view theparameters within the system and can suggest a new parameter to evaluateGame #1 (538).

FIG. 6 is an illustration of one embodiment wherein the User VolunteersProfile Information for the Benefit of Obtaining a uEffectResult/Score/Symbol Tailored and Weighted with Other Users With SimilarProfiles/Interests/Associations for Purposes of Social Networking andGathering, Feedback Sharing, and Prediction and Notification of FutureProducts, Services and Behaviors.

FIG. 7 is a dash board that illustrates how a user can search the systemto compare products, which, in this example, are cameras. There areinput parameters such as system suggestions (701), user groupassociation parameters such as 55 year old fathers (702), a utility or ause parameter such as ‘gift’ (704) and user weighted and defined searchparameters defined by the user (705-708). The result is a dynamicgraphical interface that illustrates the summary results from the searchdisplaying the various camera associations, user groups and parameterswithin the user associations and groups (708).

FIG. 8 is an example of a dash board created by a user to visualize aproduct comparison based upon the criteria set by the user (801-803) andthe weighted parameters defined by the user (804-807). The variousparameters are displayed on the graph and exhibit various symbols thathighlight the underlining value of the parameters, e.g., the color ofthe circles, the size of the circles, the placement of the circles andother defined data points (808).

FIG. 9 is an illustration of momentum trend analysis wherein parameterscan be tracked and visually displayed by inputting parameters, topicsand the weightings by specifying certain criteria (900, 904). A momentumquotient (MQ) can be quantified. In one embodiment, this system canpredict the momentum trending analysis (MTA) which can predict whichsmall businesses will be successful. One topic, for an example, would becoffee retail establishments, with a sub-topic of independent(non-franchise) stores with several parameters tracked and followed bythe suggestion of the user group and the individual users. Parameterscan then be isolated for search, trending and prediction. In thisexample, stores with month-by-month cash flow (increase or decrease)(900, 901) can be charted against average monthly income (904, 902) witha calculated momentum quotient (MQ) displayed on the horizontal line inthe middle 903. From the perspective of the ‘owner's’ user group,parameters that may be more relevant may include monthly sales trendingdata, coupled with a formula to determine the location effectiveness(parking, location next to a larger retail store, downtown, etc.).However, from the perspective of a banker who loans money to coffeeretail stores, the cash flow trending data may be more relevant to thesuccess of the store. Factors, parameters, topics can be evaluated andthe cumulative result generates the momentum trending data that can becorrelated to the actual performance of the individual stores.

FIG. 10 illustrates how users can belong to various groups andassociations and how the parameters within each user is weighted andscored to generate a summary result and a more tuned search. Forexample, a Christian 28 year old female may search for feedbackparameters about a particular movie. The system may provide a groupsummary resulting symbol (1000). The searcher may then filter and tunethe search by parameters set by the searcher based upon her own criteriaand criteria suggested by the system. Such filter and tuning may includefeedback about a particular move with the following user definedparameters as P1, P2 and P3, with certain specific weighting andalgorithms with filters including female and Christian user feedback anda further tuning of 20-30 year olds.

The system can then correlate the search request and organize the usersinto groupings of Christian, Female and 20-30 year olds (1010-1030). Thesystem can further organize by incorporating weightings intoclassifications and classes and can further organize by placing theusers and different axis wherein the closest, left-most, highest usersproviding (scoring) the most relevant feedback for the searching user.

FIG. 11 is an illustration of one embodiment of the system wherein auser has accessed the network via a personal communication device(1100). In this example, the user has previously entered in theirprofile information, their search parameters, and the weightings oftheir search parameters and has configured the system to displayfeedback from a particular user group or a user association, in thisexample, 20-30-year-old females. This embodiment is a search forrecommended movies (1101). The user has a filter of ‘previously viewed’movies wherein any of the movies the user has seen will not be displayed(1102). The user has searched the feedback recommendations from thesearch parameters and criteria for a particular movie grouping, in thisexample new releases that meet her search criteria. The ‘resultingsymbol score’ is displayed (1103). The individual, dynamic feedbacksummary scores, (uFECT.com or uEffect.com score or ranking) is displayedas faces. Upon clicking on the symbols, the underlying scores, votes,feedback and other data can be viewed. The symbols next to the uEffectsymbols are symbols are links to the content provider's (in this examplethe movie industry) movie trailers and other ‘pushed’ informationgenerated and provided by the manufacturer or the author of the movie(1104). Other user defined and system suggested search and comparisontools are available (1105) to help tune the search, compare and analyzefunctions (SCAF) of the system to make the SCAF more relevant.

FIG. 12 is another embodiment of the system wherein the usergroups anduser associations outline and define the parameters and the relevancyweighting (RW) of the parameters. The data input fields are available toaccept user input and feedback to contribute to the feedback iconresult.

FIG. 13 is an example of one embodiment of the system illustrated as aflow chart. In this example USER X initially accesses the system andinputs data. Data in some instances includes a system suggestion orprediction, in this example a user group association, wherein the userchooses one or more associations as a ‘default’ parameter. When the USERX then accesses the system via a cell phone, the defaults are storedwithin the system data base, the defaults become part of the SCAFprocess wherein the parameters, weightings, filters and tuningmechanisms are employed.

FIG. 14 illustrates in a three dimensional graphical interface thecumulative summary results of the parameters, X, Y, Z, with factors ofa, b, c, in combination with stored user feedback and other data(1401-1403, 1404-1408). The system suggestion of a SCAF results in aSCAF resulting positioning placement (RPP) of a point in the graph(1404). 1410 represents user parameters of ranking and date, with a linedepicting the purchasing momentum based upon ranking slope and/orpurchase slope contributing to a momentum quotient. Users can implementSCAF results utilizing various group members, user groups, groupclassifications, associations, and other groupings or orderings, withvarious defined parameters within the groups (1411-1414).

FIG. 15 is a flow chart illustration wherein a user, or a user group,defines groups of users, categories, parameters associated with thegroups, user input and profile data (1510), and defines the processesthat incorporate the data. The system can also incorporate the searchinguser defined processes and the database can then generate custom resultscombining the user group specifications with the rules, algorithms,filtering, tuning and parameter specifications of the user (1500).Topics are elicited and/or suggested.

FIG. 16 is a flow chart illustration of the system. In this example,data from 3^(rd) party, external sources is combined with the systemdata.

FIG. 17 is a basic system overview that illustrates user input, process,output and a feedback loop.

FIG. 18 is a flow chart illustration of the system wherein a first-timeuser inputs data about a topic, product, service, person, place, orevent.

FIG. 19 is a flow chart illustration of the system wherein a userinitiates a user group association, and inputs suggestions that beingthe process of defining rules and parameters and other processes.

FIG. 20 is a flow chart illustration of the system that incorporates theuser data input and processes the information to result in a cumulativesummary symbol.

FIG. 21 is a flow chart illustration of the system that outlines oneembodiment of the system wherein the users and the system access theinternet.

FIG. 22 is a flow chart illustration of the system enables a user to adda new parameter.

FIG. 23 is a flow chart illustration of the system that illustrates oneembodiment wherein a user interacts with the system network whileperforming a SCAF.

FIG. 24 is a flow chart illustration of the system that illustrates oneembodiment wherein a user interacts with the system network in creatingor suggesting a new search parameter.

FIG. 25 illustrates two embodiments of the system performing a SCAFillustrated by formulas. The second formula includes an added parameteror filter that represents a ‘time’ or date stamp.

FIG. 26 illustrates two embodiments of the system performing a SCAFillustrated by formulas. The formulas incorporate different group anduser defined formulas. The formulas include data from user feedbackinput and have a specific criteria in which to process the data with thevarious user (and user group) parameters, weightings, rules, algorithms,filters, and tuning variables.

Examples of Some Embodiments

Several examples and embodiments of the invention are herein describedto provide an illustration of the implementing the invention andrealizing the results of the unique characteristics of the invention.

One example of the difficulties of obtaining and determining meaningfulfeedback might be a topic of critical theater reviews. It's a known factthat certain theater critics in major markets such as New York City,wield an inordinately large influence on whether a new production issuccessful by writing a positive or a negative review and publishing thereview in a newspaper, other online media outlets, TV and radio. Sometheater critics have admitted that negative reviews are more ‘fun’ towrite, and are more read, remembered and talked about then positivereviews benefiting the author, the branding of the newspaper andadvertisers. This highlights an important point, that there are severalfactors that influence a feedback opinion in ALL areas of content reviewand validation. Influencing factors include (but are not limited to)economics, politics, business and personal factors (such as keeping ajob, or personally knowing a person to benefit or be negativelyinfluenced by a review). ‘Supply’ generated content described asfeedback has influenced many people and industries.

For the above example, the invention would elicit input from users whohave seen a particular play. The users would individually inputinformation about this topic (theater, with a sub-topic being the nameof the new play) including the parameters that they have deemed relevantfor feedback and review. Individual parameters, weightings and scoreswill be stored along with suggested parameters and weightings for acommunity or user group as a whole. Community parameters may be generalparameters to review such as ‘overall rating’, ‘story line’, ‘humor’,and ‘acting talent’. Individual parameters may be ‘recommendation forothers’, ‘nudity’ and ‘language’. The user may suggest to the user groupthat the new play is most appropriate for a ‘use’ context such as a‘guy's night out’.

Subsequent user(s) who attend the new play may access the parameters andprovide rating or scoring data on the user groups suggested parameters,and may weigh the parameters in a different priority, such as ‘storyline’ being the dominant driving parameter. In addition, the subsequentuser may further suggest additional individual parameters such as‘musical talent’ and ‘extent of the pre-performance expectations havingbeen met after post-performance’.

Still more subsequent users, can access the user group community to viewthe currently rated parameters and the scores of each parameter with thedata displayed as a cumulative summary result. Subsequent users canspecify search criteria that might include other user's profileinformation and weightings of parameters relevant to the searching user.For this example, users who view displayed data are viewing thecumulative summary results of a uEffect score or rating. The user maysearch using general parameters such as other male theater goers, overthe age of 35, who rate the new plays as ones with the highest rankingof most ‘humor’. More specific search can result in how a particular newplay was rated in general, and then give a priority weighting to how theplay was rated by a specific user group such as theater goers over theage of 35, driving down to more detail to compare the rating results ofa new play with the ratings of theater goers who are ‘casual’ theatergoers compared with the ratings of the theater goers who representthemselves as ‘avid’ theater goers. Users that contribute data andfeedback contribute to a uAffect score or rating, generating a UniversalAffect Result (UAR).

Another example is music—it's been well documented that certainproducers and record companies have engaged in a practice called‘payola’ where certain new song releases get air play based upon thefinancial kickbacks that the producers offer the radio stationprogrammers. This is but one example that illustrates an artificialendorsement where by the general public is sometimes unaware of therelevant nature of the content delivered.

The invention described herein is a system and method for improving themethod of gathering relevant feedback from meaningful sources thatinclude the users and user groups and communities (UGC) that surroundthe topic. The method includes a tool to identify contributing users andthe profiles and behaviors of each user. Users identify the parametersthat determine what information is considered relevant and meaningful tohim or her. The user then can prioritize, categorize, and assign aweighting matrix to the parameters and factors that make up themeaningful feedback surrounding a particular topic. User profileinformation, user feedback input values and parameter weightings arestored in a database.

A 45 year old male can search the topic of new music, and weigh andprioritize the preferences identified by the 18 to 25 year old users. Byexcluding his own user group or association (in this example “over 40year old males”, the searching party can identify the parameters,weightings and ratings that the 18 to 25 year old association of usershas defined as relevant, and further search what new music is arrivingon the market that has been evaluated as more relevant or positive. Thesearching party could then further search by more heavily weighing thefeedback from guitar player/musicians who are listening to new music. Amechanism within the apparatus provides a forum that suggests otherusers with similar parameters and/or weightings, and enables the user tocontact (at times anonymously) other users who have a particular profileand has posted similar weightings and parameters on certain topics. Inthis example, users of similar profiles may belong to a multitude ofassociations, including ‘age group’, ‘male’ or ‘female’, ‘new musicenthusiasts’, ‘country-rock genre’ primary, ‘folk genre secondary,‘armature music industry purveyors’, ‘electric-guitar players’.

Users further enhance the feedback matrix by defining rules andalgorithms, and initiating, prioritizing, categorizing and assigningweighting values that define the parameters and factors for the UGC as awhole regarding a topic. This illustrates how the system managescollecting, organizing, managing and weighing the relevant factors onindividual users and the overall parameters of the user group using auser-centric, predetermined formula to generate a cumulative summary,score or result. Such a technique in some embodiments is similar innature to the Delphi technique.

In some instances, gathering input information when initially definingparameters to benefit the community or group as a whole, the process mayinclude such tools as the Delphi technique. The Delphi technique is amethod for obtaining forecasts from a panel of independent experts overtwo or more rounds. Experts are asked to predict trends, quantities orother data. After each round, an administrator provides an anonymoussummary of the experts' forecasts and their reasons for them. Whenexperts' forecasts have changed little between rounds, the process isstopped and the final round forecasts are combined by averaging. Delphiis based on well-researched principles and provides forecasts that aremore accurate than those from unstructured groups (Rowe and Wright 1999,Rowe and Wright 2001). Such a technique can be implemented in theinvention with the ‘administrators’ defined as a user or a group orcommunity of users.

Generating a score that more effectively reflects the relevancy of thecontent is predetermined by the user group and can be summarized in asymbol that reflects multivariate parameters and values. A resultingsymbol is generated by the system and is configured to best serve theuser group in an easily recognized fashion whether accessing the datafrom a computer, mobile phone or other communication device. Such aconfiguration may take the form of a line-association and/or a bubblegraph that represents several, multivariate, weighted variablesaccording to the underlying values or scores.

Using any communications device that can access the internet, users canat any time log on to the system and have displayed the resulting symboland have interactive system access to the details that determine theresulting symbol. By clicking through on the symbol, the user can viewthe determining parameters that make up the result, and the cumulativevalues assigned to each of the parameters. Symbols or results can bedisplayed in a simple format in one embodiment for cell phones whereinonly the space of one or two digits is used.

For example, if the output is a symbol in the form of a capital letter‘A’, and multivariate parameters and scores can be identified usingdifferent display options, then an underlined ‘A’ may represent thecumulative search summary result of the most relevant feedback from theperspective of the user group as whole. The color of the digit ‘A’ mayrepresent cumulative search summary result (CSSR) of the most relevantfeedback from the perspective of the defined and weighted parameters setby the searching user with red being most relevant, blue being the leastrelevant. Other display options that may represent additional data inthis example is an italic or bold font, the background color of thedigit, and other audio and visual adaptations of display. Other types ofmultivariate symbols that might be applicable for a cumulative, weightedsummary result (CWSR) display on a PDA or cell phone include thesunflower plots and the Chernoff Faces. Chernoff faces displaymultivariate data in the shape of a human face. The individual parts,such as eyes, ears, mouth and nose represent values of the variables bytheir shape, size, placement and orientation. The idea behind usingfaces is that humans easily recognize faces and notice small changeswithout difficulty. Chernoff faces handle each variable differently.Because the features of the faces vary in perceived importance, the wayin which variables are mapped to the features should be carefully chosen(Herman Chernoff (1973). “Using faces to represent points ink-dimensional space graphically”. Journal of the American StatisticalAssociation 68 (342): 361-368.)

Online user community example: One illustrative example involves thefield of new product launches. The challenge in this illustration isspecific to a 28 year-old female video game player. When a new softwarevideo game is released there is a frenzy of people that provideinformation and feedback to review the game. However, the reviewsoffered and posted by people, communities and businesses are ofteninfluenced by several factors, not the least of which can be economical,political, personal, business interests and more. In this embodiment, avideo game manufacturer may target market most new video game productsto audiences that include the 14 to 28 year old males. This inventionhelps this female video game player to best determine if this specificrelease matches her preferences and would merit purchasing over othervideo game options. The female gamer can view general scores, ratingsand feedback from various user groups or data collectively, but thefemale gamer would benefit most to hear or read feedback from individualusers that better match her profile and her defined and weightedparameters of relevant feedback or reviews. Examples may includefeedback from other 28 to 30 year-old females who enjoy the same orsimilar types of video games, and excluding feedback from other usergroups and associations such as males under the age of 28. Such feedbackis welcomed as more meaningful and relevant information then from a malemagazine critic or blogger who may be a 21 years old.

The invention enables the CSSR and CWSR symbol(s) to be active dynamiclink to the network. Consequently, in some embodiments, the CSSR andCWSR symbol displays elicits and receives information. In oneembodiment, the CSSR and CWSR symbol is a real-time, interactive linkvia the internet (e.g., an internet enabled cell phone or PDA).

There are a number of searching tools available to such a gamer lookingfor relevant information, but the sheer amount of feedback andinformation is often times overwhelming. There may be a list of blogsfor example that are displayed from a search result. But which blog ismore relevant to the female garners group. Currently ‘relevant’ contentis rated on just a couple of factors that include factors such as thenumber of downloads or visitors to a site/blog with some examples ofconsumer or searching behaviors are tracked and influence a result basedupon criteria defined by the website author, content aggregator orsearch engine. However, these numbers are often skewed by using severaltactics including hiring marketing promoters who hire people toartificially inflate these factors by clicking through or downloadingcontent for no other reason but to generate activity that is thenartificially reflected in the ‘relevancy’ of the ratings.

The invention is a system that is described herein, providing a methodwhere feedback is gathered from other users (to further illustrate theexample above, other female games who are 28 years of age). The feedbackgenerated and collected by the other garners is rated and scored basedupon parameters that have been previously determined, by an associationof users (in this example a user group of 28 year-old female garners),to be meaningful and important. This data is then enhanced by theprofile information offered by the individual users and stored in adatabase. One example of a parameter within this topic may be ‘nudity’,a parameter that may have a different relevance priority to 28 year oldfemale garners when compared to 18 year old male gamers as a group.There may be sub-topics associated to nudity such as male nudity, femalenudity, sexual acts between nude males and nude females, violenceassociated with nudity and others sub-topics or factors defined by theuser or the user group.

The feedback values, or scores, from the various factors within a topicare solicited from the individual users. Feedback values about therelevance priority of the individual parameters are solicited from theindividual users. This data is then combined with the profileinformation from the female, 28 year-old user group, is then organizedbased upon the previously determined rules, matrix and factors, and thenis displayed via a number, symbol or other easily recognizable markerthat also can be determined by the user, user group, or the associationas a whole. This marker is then available for display on a website andis available as a software code script for downloads and display onother personal computers, websites, web pages, blogs, search resultengines and other content aggregators media outlets. The notificationfeature of the system will enable the 28 year-old female gamer to benotified of feedback, or changes to feedback, based upon the rulesprovided by her previously. In this example, one rule set may include anotification if there is a new product release that receives positivefeedback that meets her requirements and the requirements of the femalegaming user group or community. Notification may take the form of ane-mail or text message on her cell phone (or other preferrednotification option defined by her) of the status of the rating and/orthe status of a resulting symbol. The notification script can bedownloaded onto a personal computer or other communication device, or itcan be hosted within the system and network.

Offline user community example: An example of an offline topic (or anon-internet or web-driven) example might be live comedy feedback andcontent reviews. Take for example a business traveler on the road whowill be spending a couple of days in Chicago. This traveler enjoys livestand-up comedy, but is adverse to profanity used by comics. The systemdescribed herein will have a portal assessable via cell phone or othercommunication or input device that displays feedback about comedians andtheir routines. The traveler will be able to view and access feedbackgenerated by his predefined parameters to determine which comedian withperformances in Chicago may be more appropriate for the traveler.Continued searching within the system incorporated with this inventionwould further provide feedback to the traveler, from other users, as tothe appropriateness of a specific comedy routine for a particular user,in this example a ‘use’ or ‘utility’ mode, may be defined as a guest(romantic date) or employer of the traveler to attend the comedy routinewith. Based upon feedback and content gathered from others in his usergroup, the traveler may feel comfortable to invite a co-worker or a dateto the comedy routine. The content will have the resulting summarysymbol, and will also have access to the profanity factor values thatare easily displayed on a web enabled cell phone screen.

Users can provide and input feedback on each of the factors within atopic and can also input and create additional factors within a topic.In this example, the business traveler may access the system, and inputan additional factor within the ‘comic routines’ topic, and for thisexample the traveler enters in a ‘use’ or ‘purpose’ parameter, creatinga different factor for other users to be aware of, and for other usersto have the opportunity to provide feedback values. The traveler maycreate sub-topics to include: ‘purpose: guy's night out’, ‘purpose:first dates’, ‘purpose: out with employer’, ‘purpose: out withson/daughter’, ‘purpose: date with wife’. After attending the comicroutine, the traveler may provide a high scoring, weighting or value tothe ‘purpose: guys night out’ because the routine included funny jokeswith sexual innuendoes that guys enjoyed, but may provide a low scoringto the factor of ‘purpose: out with son/daughter’, and ‘purpose: outwith employer’.

The system and method enables the users to benefit from the stored userprofile information of the individual users and the user groups andcommunities as a whole with the ability for a user to change their userprofile to benefit subsequent searches by the user and for the benefitof predictability tools. In one embodiment, a 45 year-old male may notbe interested in the new movie reviews that other 45 year-old males aremore inclined to provide feedback scores on. Instead, while preferringaction movies with a particular young actress that typically attracts ayounger move going audience, the 45 year-old user may tune his searchthe cumulative results of movie reviews from the younger 20 to 25year-old group, with a sub-topic of a particular actress, with anothersub-topic to further tune the result to the name of the actress.

To further this example, the 45 year-old user finds the feedback fromthe younger 20 to 25 year-old age group to be more meaningful then whatthe 45 year-old age group provides. If however, the 45 year-old user hasa religious experience and no longer is interested in the feedbackreviews from the 20 to 25 year-old movie goers, he can change hispersonal profile and weightings to reflect his religious aspirations andchange his search queries to reflect this change. The user may decide tosearch for new movie releases that move goers in the 30 to 40 year-oldgroup who prefer family orientated, and religious themed movies thathave provided positive feedback. The user would also have the ability toincorporate, with defined parameters and weightings, in his searching,comparing (and contrasting), and analyzing feedback with the input andfactors of another user group or association such as a family religiousgroup.

To further tune and enhance the relevancy of a search result, the user(or a UGA as a collective) can change the matrix and the algorithm ofthe values assigned to the parameters and topics and how the values arethen reflected in a CSSR or CWSR.

Utilizing the predictability tools, the system and method may generatesearch results and notification text messages to the user that thesystem may recommend based upon the user profiles and parameters thatthe user specifies. Correlating user profile and feedback informationdata in this example is then organized to provide other recommendationsthat the user may benefit from. In this example, the 45 year-old user,after changing his personal profile values for ‘religion’, may search orbe automatically notified of new music CDs released by Christian artiststhat have received favorable reviews from both the 30 to 40 year-oldgroup and the 45 year-old group and is recommended by the familyreligious group.

A further enhancement of searching for meaningful feedback would be thesame 45 year-old movie goer searching for suggested movies by other 40to 50 year-old users who recommend new movie releases for a specificoccasion. For example, new releases that would be appropriate for firstdates, taking a son or daughter out, or a ‘guy's night out’ type ofmovie based upon the predetermined parameters deemed meaningful andrelevant to the 45 year-old movie purveyor and the relevant parametersdeemed meaningful from the user group or association of 40 to 50 yearold movie goers.

To further highlight the unique aspects of this invention specific toproduct searching and reviewing, the user can specify searchcharacteristics to include parameters that the user deems meaningful forproduct searches. To initiate a search for cameras, the user would bringup a dashboard like input screen, see FIG. 7, the uEffect.com cumulativeweighted results search page (CWRS). The input topic, parameters andfactors would be inputted in this embodiment as follows;

The topic is inputted at 701, and the search function ‘look it up’ isselected.

The association the user belongs to and the searching function is theparameters in 702. Editing capabilities exist to change the data inputprofile. Note that in this example, the searching user is not comparingproducts, see FIG. 8, but searching relevant feedback information aboutparameters identified by other users and user groups as relevant.

Options to ask questions, and or elicit feedback from other users withsimilar profiles or other predefined parameters inputted by the user canbe found with the function items in 703.

704 identifies the search mode and a utility function, for this example‘gifts’ is inputted. Search results will tailor the results for the userbased upon collected information from other users and user groups aboutthe relevant parameters involved in the topic of cameras, for the“utility” of a “gift”.

705 represents the resulting sub-topics that the system suggests andpredicts as meaningful and relevant and is displayed with links to theunderlying information that formulates the suggestion.

706 is a data input and weightings for the ‘My Parameters’ function ofthe invention. Drop-down menus provide historical parameters that theuser has used in the past and the system then also suggests and predictsparameters that may be relevant based upon previous searches from thisuser and other users with similar profiles who belong to a similar usergroup or association. In this example the user group may have weightedthe parameter of storage capacity as a more relevant factor inconsidering a purchasing decision.

In this example, 706 pricing is weighted as a ‘9’ on a scale of 1 to 10with 10 being the most relevant. Storage capacity is a meaningfulcomponent of the search and is weighted as a ‘3’. New parameters can beentered and weighted.

707 formulates other user defined search criteria. Drop-down menusenable the user to easily identify relevant search criteria with helpfrom the system and apparatus. The system suggests and predictsparameters based upon several factors, previously defined by the user orthe user group, from information stored in the database. In thisexample, ‘My Parameters’ are rated as a ‘9’ in a scale from 1 to 10,with 10 being the most relevant. Other influencing search filtercriteria includes the ‘Amateur Camera Assn.’ feedback and input and isweighted as a ‘3’ by the user. The user has the capability to excludespecific input data or parameters and in this example, the data gatheredby the ‘Professional Camera User’ association is omitted.

708 Profile and additional search criteria can by configured by theuser. In this example, ‘Pre-Purchase Parameters’ are highly weighted asa ‘10’, ‘Post Purchase’ parameters are omitted with a ‘0’ weighting, thesearch is optimized and filtered to include only users who have beenauthenticated by the system (authentication includes different levels ofuser data access and permissions based upon criteria that the usercommits to upon the varying levels of authentication). This filter thenwill only include the feedback data from the users who have beenauthenticated by the system as meeting and committing to certain levelsof participation with the uEffect/uAffect system. A time element isfurther added to tune the search in 708, by searching only feedback hasbeen provided within 1 year.

709 represents a tailored, customized and weighted search result fromthe parameters and definitions supplied by the user. In this example,the user has opted to have the results displayed with a graphical lineand object representation. Users can opt to view data in a systemprediction and suggested format or the user can define in their profilea specific representation style, graph, symbol, audio attributes andother embodiments, see FIG. 8 for a bubble graph option. In 709, thesize of the circles represent the output relevancy of the topics andparameters. Other weighted attributes are colors, font size, sounds,font styles, line types (dotted or solid) and sizes and other visualaids.

The resulting 709 search illustrates that there are sub-topics relatesto cameras, including pinhole cameras and digital cameras. Clearly, thedigital camera results are more relevant than the smaller circle thatrepresents pinhole cameras results.

709 also represents the relevant associations that have been formed byother users and are affiliated with cameras including ‘Hobbyists’,‘Amateurs’, ‘Weekend Shooters’, ‘Dummies’ and ‘Professionals’.Parameters have been identified within each of the associated groups,and some parameters, such as ‘price’ are linked as relevant to more thenone association of user groups. ‘Amateurs’ is highlighted for thesearching user and ‘ease of use’ is a relevant factor that is identifiedas important to this user group, just as ‘focus’ is identified by‘Weekend Shooters’ as a factor to be considered relevant along with‘standard battery’ options. The users identified as having little or noknowledge of cameras and have feedback relevant for future usersattempting to gift a camera to someone have identified ‘return policies’as a meaningful parameter.

When the searching user moves the cursor on his screen to the ‘Amateurs’circle, a pop-up window appears with links to other relevant informationthat the system has suggested and predicted to be meaningful to thesearching user. In this example, the following links are provided in710; Amateur Users Relevant Parameters and Scores, Recommended CamerasModels by Father's Association, Suggest Camera Models to Father'sAssociation, List ‘over-all Best Buy’ by uEffect relevancy, List‘over-all Best Buy’ by Price, and Manufacturer Recommendations. Each ofthese links represent links to collected and stored information fromother user groups that have identified, defined and weighted relevantparameters based upon their respective backgrounds. Users, in thisexample, are identified as individuals as well as industry members as‘Manufacturers’.

In this embodiment, the ‘manufacturers’ link is connected to data aboutthe cameras that have been authorized by the manufacturer of each of thecameras. This data includes the details of the camera specifications andalso includes the marketing and sales information the manufacturerdecides to provide. The source data can be hosted on the manufacturer'swebsite or database or can be uploaded to the uEffect system anddatabase by the manufacturer or by a uEffect user or automatically bythe uEffect system.

For this illustration, the multiple editing functions also include aneasy user interactive interface that enables the user to tune andoptimize a search result. 711 is a list of icons that enable the user toorganize the resulting items. In this example the drag and drop featuresenable the resulting search items to be placed into a trashcan, a spam“can” or similar folder, or a clipboard to save items.

For example, if a 45 year-old is trying to find relevant feedback aboutnew digital cameras on a commercial retail website, and the websiteemploys the system and method contained in this invention, the 45year-old user can specify searchable parameters important from hisperspective. The user can search for meaningful feedback that entailssearching for cameras that have easy-to-use navigation of the onboardmenu options—from the perspective of users whose profiles indicate thatthey are novice camera users—and search results that address the autofocusing feedback from users who indicate that they are professionalusers in their profiles.

Advertising feedback for businesses example: The commercial componentmodule includes the ability for advertisers to gather feedback fromindividuals associated with the System. In the example above of thefemale gamer, the system will provide an opportunity for feedback of aparticular ad or advertising campaign. The feedback will come completewith the user profile and other such information that is voluntarilyoffered (the female gamer could vote or rate an ad based upon predefinedparameters and the advertiser would be able to garner the feedback aswell as the user profile with or without information includingmale/female, age, location and more).

If the advertiser of a new video game release displays a prominent adonline at a particular website, there would be included at the bottom ofthe ad a link to the system feedback module (SFM). If the 28 year oldfemale gamer came upon the ad, and wished to provide feedback to theadvertiser, she would click on the link, and rate or vote on theparameters set by the advertiser (example parameters might be: rate theeffectiveness of this ad over other video game ads, based upon the ad,would you recommend this video to a friend?). The option will exist forthe female gamer (or the UGA) to suggest and create a parameter of herown, potentially including a rating on the effectiveness of violent orsexually explicit graphics. If voluntarily offered by the female gamer,the advertiser would have access to the feedback provided by the femalegamer as well as background information embedded in the female gamer'ssystem profile including such information as age, location user groupaffiliations, previous behaviors and scoring patterns, and other user(or UGA) data.

Commercial feedback example: Another application of the System would befor consumers to rate businesses (products and/or services) and thereverse: businesses rating or scoring consumers (e.g.,BetterConsumerBureau.com).

One example would be for the system database to gather and collectrating, voting, scoring on relevant information collected bybusinesses/consumers on their experiences with their respectiveconsumers/businesses. A ‘credit score’, a ‘behavioral rating’ (BR)score, or a combined ‘credit and behavioral score’ (CBS) is created withpreviously determined parameters defined by the users(consumers/businesses) with the results posted for access to otherusers. The user community would then have the opportunity to providefeedback on their experiences with the particular consumer/business.Users in this example may have different verification levels that enablethe user to access and contribute data at different levels, depending uptheir respective verification level. A combined and weighted outputmeasurement can be determined with the output being a symbol thatcombines the underlying rating or score of the particularconsumer/business.

Statistical and modeling tools and algorithms can then analyze thecollected information and provide prediction and trending data for theparticular consumer, business, product or service being evaluated by theusers. A momentum quotient (MQ) can then be defined and displayed in asummary symbol for access and display to users and user groups upon apredefined user access and validation rules set. In some instances, theMQ may be defined as the slope of a trending line or a space distance ona chart.

The invention can be utilized to determine a uEffect Momentum Quotientfor an event such as a music concert that is being performed in severallocations throughout the year, a show or a campaign like a politicalcampaign. In a political campaign, users can post the issues, topics andimportant parameters that are important to them, and then rate and scorethe candidates responses to the issues and parameters. The priority andthe weighting of the user's issues and parameters can be compared andcontrasted to the candidates' posted priority and weightings of theirown identified issues and parameters. The cumulative summaries, througha user defined algorithm, can be then displayed as a momentum quotientof the various candidates as well as the specific issues and parameters.

Various levels of validation, access and input can be identified in apolitical campaign embodiment of the invention. For example, the generalpublic may have access to the momentum quotient of the candidates andthe general parameters. For users to desire to view additionalinformation, they may be required to become validated by a rules setdefined by a user group or an association of users. Once validated, theuser can then have access to information from a uEffect momentum result(MR) including the issues and parameters detailed scorings and ratings.A user, for example, may have access to details of what males in the 40+year old association have identified as their first priority issue suchas the economy. This information can be compared and contrasted toinformation about females under the age of 40 who have noted socialsecurity as their number one priority issue.

Information about how certain groups are providing feedback aboutdifferent candidates can be accessed, such as the uEffect Momentumquotient for each of the candidates for the over 65 year olds, versusthe uEffect quotient for each of the candidates from the 18 to 40 yearolds.

In the above example, Paul Sadler, an individual user, may view asummary symbol of the momentum quotient for a particular candidate. Byvalidating himself as a user according to predefined rules, he mayprovide his e-mail address to validate himself to a level 1 access. Thisaccess may enable him to view more detailed information such as theunderlying details that make up the summary momentum quotient for thecandidate he is interested in. Details of each of the issues that thecandidate have posted, weighted and has prioritized, and the issues thatthe user groups and associations have posted, weighted and prioritized.By further validating himself, Paul would have access to moreinformation and would be able to contribute to the scores and ratings.For example, according to the predefined rules set, if Paul wouldprovide his zip code, age, and gender, he would be permitted to accessan input screen to provide ratings or scoring information on the variouscandidates and issues currently displayed. He may also have the abilityto score and weight the various issues according to his own prioritiesand have the scores and weights contribute to the overall scores andfeedback about each of the candidates and the issues surrounding each ofthe candidates and the general issues that have been identified by theuser community.

Further validating his user status, Paul would have access to otherusers who have elected to be included in the system forum and socialinteraction component of the invention. This would enable Paul toassociate himself with other users who have a similar profile, otherusers in his home community and others who have similar weightings ofthe issues and candidates. Paul will have access to an association pagewherein discussion forums are hosted by the system's apparatus and hewill be able to post, chat and communicate with other individual usersand post comments to the discussion bulletin board.

If the UGA of the above example wants to offer an option to solicitcandidate information from subsequent users, the UGA may configure thesystem to first ask for the candidate the user supports. Then the usercan specify the issues and weight, score and vote on issues and otherparameters. The user then has the option to compare the user'spreferences to other UGA(s) (e.g., UGAs that incorporate user profilesand other inputted information, to also include the summary result fromthe composite UGAs combined).

Method of Claim AA—business Momentum Analysis example. An example of asystem and method to evaluate the success of a business model employingthe tools of Momentum Analysis would be independent coffee retailstores. User groups, including store owners, academics fromuniversities, professionals such as accountants and bankers, woulddefine the parameters that define successful operations based upon theirrespective profiles. As time passes and data is collected, theindividual factors within the parameters are evaluated by all parties.The method is configured to obtain data and forecasting information withseveral, real-time updates. Summaries of the relevancy of the parametersand the values of each of the factors within each parameter aredisplayed of the relevancy of the parameters and factors weighted as anoverall average and weighted to each of the user groups. Statisticalanalysis is then employed to determine an overall, cumulative summaryresult or score.

For store owners, relevant parameters may begin as location, service andquality. As additional data is collected from additional store owners,and as the store owners evaluate the parameters, some parameters mayemerge as more relevant, in this example, quality may eventually surpassservice.

For professionals including bankers and accountants, working capital andcash flow may be more relevant parameters then service. Cumulativeresults and values are displayed to each of the user group according totheir individual profiles, as well as a cumulative summary of all users.

As additional users continue to further define the parameters, therelevancy of each parameter, the individual factors within eachparameter and the overall scores contributed by each user, the databecomes statistically more accurate for user-centric momentum analysis(MA) and momentum predictions (MP).

Method of Claim AA—business peer evaluation example. An example of thesystem and method is in peer evaluation techniques. Take in thisembodiment mid-level managers at a large company and their supervisors.The desired result is the evaluation and forecasting of leadershipskills in individuals at both the mid-level management level and thesupervisory level. Each mid-level manager and supervisor would input hisor her individual profiles into a database. The parameters of anevaluation can be collected by both sets of users, the mid-levelmanagers and the parameters of the supervisors. Parameters can beorganized where the system and method, or an individual or a group, actas a facilitator of the collected data, displaying the weighted resultsof the parameters of the mid-level managers compared and contrasted tothe weighted parameters of the supervisors. Parameter sets are thenevaluated on two or more rounds to eventually settle on a predeterminedset of weighted parameters in a priory list.

All users can then score or set a value to each factor within theparameters. For example, the mid-level managers evaluating supervisor'sleadership skills may begin with predefined parameters in a weightedpriority of: listening skills; over-all attitude; and collaborationskills. Each mid-level manager would then score their supervisors, upona facilitator or user-defined rating scale (or suggesting an improvedrating scale), detailing how their supervisor measures up with each ofthe factors. Overall results can be displayed as well as specificqueries weighted and organized collectively with input from theindividual user's profiles. One specific query would be the summaries ofwhat mid-level managers under the age of 40 collectively considered themost important parameters, compared with mid-level manager's parametersover the age of 40.

Conversely, supervisors could detail the parameters that they considerkey characteristics of identifying leadership skills necessary todevelop into upper management. Parameters are solicited from allsupervisors, organized and weighted by the system or a facilitator, fordisplay for further evaluation of all supervisors. Collectively, as auser group with the aid of the system and facilitator, the supervisorswould agree on the priority and weightings of the parameters for eachtopic and/or category. Individual factors and a rating or scoring scalewould be agreed upon collectively by the group or provided by thefacilitator. Scores for each of the supervisors can be then collectedbased upon their experience with managing their respective mid-levelmanagers.

Overall results pertaining to the mid-level managers can be displayed aswell as specific queries weighted and organized collectively andinfluenced by including the individual profiles (and the respectiveweightings and ranks of the user) of the mid-level managers. Data can beoptimized by further evaluating the collected information, data-miningkey information and trends to establish different parameters, factorsand/or rating systems. Information can be collected and compared againstdata collected by other divisions within the company, and compared todata collected by other companies in the same or different industries.

The relevancy of the data collected can be enhanced by factors such asthe amount of data, the time elapsed between data collection and input,and other analytical tools to continue to further define relevant andmeaningful feedback. Historical data can be compared against actualresults obtained, for example, of the mid-level managers that ended upobtaining an upper management position, what we're the parameters,factors and scores that the individual had previous to obtaining theupper management position. Comparing the results to others who haveachieved upper management positions would then be collected anddisplayed as a cumulative result with the ability to query results basedupon the profiles of the individuals involved.

Method of Claim AA—individual user and a retail experience using RFID.If an individual user chooses to provide profile information andrelevant and meaningful parameters to be stored in the system and tofurther to stored in a communication device, in this embodiment an MP3music player with RFID, then the predetermined relevant and meaningfulinformation defined by the user can be communicated to a retail storeinput device.

If a retail store utilizes an input device that can read the profileinformation, in this example via RFID, and relevant and meaningfulcontent defined by the user, the retail store's input device canrespond. One such response is a real-time video display of products thatmaybe on sale that best matches the score of the incoming individual atthe entrance to the store. In this example, a 45 year-old movie goerwith one son who owns a Sony PlayStation video game console, may beshown the sale price of a new release of a video game, with thesuggestion of a potential birthday gift for the upcoming birthday of hisson.

Anti-Fraud Measures

In some embodiments, anti-fraud checks and measures are applied to thesystem to that incorrect or maliciously data isn't intentionally passedinto the database. Typically users are entering the system resources andtuning their search, comparing and analyzing results and trends ofdetermining relevancy are identified by the system. If however, multipleusers provide conflicting feedback and data, an arbitration system maybe employed to determine the validation of the users and their purposefor providing the data and the feedback. The system may maintain IPaddresses within the user profile information and the historicalinformation provided by the users to ensure the consistency and theabsence of fraud. Another measure is the system performing a comparisonanalysis of the user with other heuristic data to determine if thatparticular user is attempting to decrease or increase a score, weightingor ranking of a user group result or a user association result.

The user (or group users) may suggest and implement via the system andnetwork other available external sources and methods to help mitigatefraud. User profile information can be checked against a telephonenumber or credit card database. Behavioral tools, such as bonding usersor insuring users and agreements may be utilized. Other technology,hardware and software can be user suggested and implemented within thesystem.

Detailed Description of the Invention the System and Method

The inventions in some embodiments comprises of a computer serverconfigured to gather data from a plurality of sources for compilationinto at least one searchable database that is accessible through acommunications network. Wherein the computer server is communicativelycoupled to a plurality of clients over the communications network, andwherein the server includes:

-   -   a data input device;    -   a business rules and data processor;    -   a data base;    -   a data output content device (and/or a display manager); and    -   profile management device        wherein the data input device, the business rules and data        processor, and the data output content device and profile        management device are coupled together with at least one        database.

Some embodiments of the invention include an apparatus that includes acomputer server configured to gather data from a plurality of sourcesfor compilation into at least one searchable database that is accessiblethrough a communications network, wherein the computer server iscommunicatively coupled to a plurality of clients over thecommunications network, and wherein the server includes: a data inputdevice configured to elicit and receive input data from the plurality ofclients, wherein the input data includes both a user profile thatincludes relevancy weights for each of a plurality of ((topics,parameters, factors, elements or other subject headings)), and user((ranking data associated with each of a plurality of entities)); adatabase configured to store the input data in a manner that retains anoutput device that gathers data from the database and presents refilleddata to the user based on the user's profile; and a data output contentdevice (and/or a display manager) and profile management device.

In some embodiments, the system supports the method and functions ofmanaging meaningful data content, including; collecting, searching,organizing, processing, compiling, computing, categorizing, storing anddisplaying distributing meaningful content that is provided and inputtedby the users (or a group of users sometimes referred to as a communityof users or an association of users). The system and method benefitsclients and other users who desire to search and obtain meaningfulfeedback authored by other users with the ability to remain connectedwith users who have a similar, correlated user profile through a socialnetworking environment. Wherein the social networking aspects of theinvention are facilitated and managed by the system based upon rules andinstructions predetermined by the user and/or the user groups.

The system that embodies the invention utilizes a communicationsnetwork, commonly referred to in one embodiment as the internet. Acommunications network may also include an intranet, wireless and mobilenetworks and other input and display devices using a variety of methodsof communication often times utilized with consumer electronic products.

Another aspect of the invention is a system comprising a computer servercommunicatively coupled to remote clients over the communicationsnetwork, wherein the system gathers and captures data for a plurality ofsources for compilation into a searchable, comparable, analyzable andeasily accessible database server, that is either locally or remotelyhosted, and connected through the communications network.

In some embodiments, the system includes methods comprising: managing(relevancy ranking in a user defined and user weighted method) andsearching and comparing meaningful data or content is a user defined anduser weighted method.

In some embodiments, the system and method performs a variety offunctions including;

-   -   a. Eliciting and receiving relevancy-weight data from a user;        and adjusting relevancy weights of ranking data based on an age        (time element or parameter) of the ranking data;    -   b. Eliciting and receiving relevancy-weight data from a user;        and adjusting relevancy weights of ranking data based on a        plurality of user-defined distances within a parameter space.    -   c. Eliciting and receiving relevancy-weight data from a user;        and means for adjusting relevancy weights of ranking data based        on a plurality of distances within a user-defined parameter        space.    -   d. Eliciting and receiving relevancy-weight data from a user;        and means for adjusting relevancy weights of ranking data based        on a context of the proposed use of the relevancy-weighting        ranking.    -   e. Providing access to users who can access and input topics,        parameters, factors, elements, scoring and other meaningful,        data into the database(s), for immediate display of processed        results for the benefit of other users or user groups who desire        to obtain meaningful content and feedback in a user defined        weighted method.    -   f. Prediction and suggesting content based upon user profile and        inputted and previously inputted data authored by the user.    -   g. Hosting a networking and communicative environment to link        users with other users who have identified similar parameters,        weightings, profiles, scores and rankings.

The invention incorporates an apparatus wherein each of a plurality ofusers can adjust relevancy weights of ranking data based on which of aplurality of user-selected usergroups the ranking data came from. Inanother embodiment, the apparatus can enable each of a plurality ofusers to adjust relevancy weights of ranking data based on a context ofthe proposed use of the relevancy-weighting ranking. The apparatusenables each of a plurality of users who can adjust relevancy weights ofranking data based on a plurality of user-defined distances within aparameter space. Thus enabling each of a plurality of users who canadjust relevancy weights of ranking data based on a plurality ofdistances within a user-defined parameter space.

In yet another embodiment, the apparatus of the system allows foruser-selected relevancy weights to include selections from a predefinedlist of relevancy weights. This also includes embodiments wherein thelist is based on a defined usergroup of like-situated users determinedby an apparatus from parameters obtained from the user's profile (systemputs the user into a group).

In some embodiments, the apparatus enables: the user-selected relevancyweights to include selections from a predefined list of relevancyweights that is based on a defined usergroup of like-situated users,determined by the user from a list of groups supplied by the apparatus(user puts himself or herself into a group); the display andmodification of user-selected relevancy weights that are inputted by theuser and user-selected relevancy weights that are generated by thesystem to form a list that can be modified by the user.

In some embodiments, as the user begins a search, a comparison, oranalyzing function, the system can present, suggest and predictmeaningful content based upon predefined logarithms and heuristicsmethods that incorporated previous data the user (and the user group'sdata) has inputted including profile information, past user behavioralsearches and comparisons, weightings and priority settings of userdefined parameters and scoring (or rating, voting or other valuationsymbols). The system searches, elicits, receives and displays contentand scoring results that incorporate user inputted parameters andweightings of parameters, and profile information in a weighted formatand method. Data is presented, displayed, and stored in a reciprocal,weighted method demonstrating the relevant results from topics orcategories inclusive or exclusive of corresponding user or user groupprofile information. Displayed data in some embodiments represent acumulative summary that can be represented in a graphic symbol, visual,or audio means with some graphical symbols representing multivariatedata.

Some embodiments of the invention include a method where the input dataprovided by users can be managed by the system server, for managing thecollecting, organizing, processing, compiling, computing, categorizing,searching, comparing, storing and displaying distributing meaningfulcontent provided and inputted by the users, or a group of users as awhole. The system then combines and stores this data with data collectedby other users who are affiliated as a small or large group, or who arerandom in relationship to the inputting users.

In some embodiments of this method, the weightings of each parameter aredefined and assigned by the user, and are stored in the database alongwith other pertinent user profile information, with the following methodand functions:

The system can elicit, receive and store the user defined parameters,rules (algorithms), and definitions of what constitutes as meaningfulfeedback, of a particular topic, sub-topic, element or factor, from theperspective of the individual user. The user-centric, user-controlledand user-defined definitions of each parameter is stored in ainteractive profile database of the user to be compared, combined orexcluded with other users' profiles and parameters of the same orsimilar topics.

The invention embodies a method in one example, wherein a user (from apredefined user group, from a randomly affiliated user group, anorganized user group, or a content provider, author, or managing entity)has the option and capabilities of predefining the data collectedincluding the data fields, parameters, formulas, and rules set ofgathering the specific data to be inputted for current and futurecontributing users of the data. Inputting user(s), in defining the rulesand or parameters, provide details of the formulas and/or rules set forthe purpose of further defining meaningful and relevant content andfeedback managed with the help of data input task scheduler (DITS).Formulas and/or rules that outline the parameters of obtaining,organizing, processing, compiling, computing, categorizing, and storingof the inputted data are for the benefit of future users who desireaccess to the feedback to improve their meaningful and relevant searchresults.

The method in one embodiment of the invention includes facilitating userfeedback pertaining to searching and comparing meaningful and relevantfeedback from other users. Contributing method and tools for users toprovide feedback is triggered in response to a users selection of theinput mode (uAffect mode) which activates the user interface with thedatabase and the user profile information,

The search and comparison results can then be manipulated in real timeand interactively, based upon the user-defined parameters using are-ordering interface, and can then be organized based upon the rulesprovided by the user or the user group(s).

A method can employ some embodiments that integrates user scoring andfeedback data in conjunction with the searchers' user profile with asearch and/or comparison query. Results are then sorted, displayed andstored in accordance with user input. An interactive user interfaceenables a user to drag and drop, preview, and organize results in arelevant and meaningful way.

The system, in some embodiments, can elicit and receive definitions ofwhat constitutes as relevant, meaningful parameters and factors in whichto evaluate topics or parameters of a subject matter, from theperspective of the user (or from the perspective of another user type orgroup), for the purpose of defining and creating a weighted,categorical, comparative and evaluative matrix of such topic for thebenefit, search and display to the user, user group and community as awhole.

The system, in some embodiments, can elicit and receive inputinformation from the user(s) including scores, values, and otherrelevant and meaningful information that correspond to the user-defined,user-weighted definitions and parameters of topic or subject. Data isstored in such a method that enables the data to be correlated to thevalues presented with the weighted user profile information in theinputting or searching user, incorporating the user defined and userweighted topic information, to be included, excluding and/or compared orcontrasted with the results of other users and the weighting(s) each ofthe other users have defined for the benefit of searching suchrepository in a customized, user-centric, user-weighted, hierarchical,and evaluative method(s).

The system, in some embodiments, can enable an author or other providerof content and data and/or the user can specify input and/or searchparameters that dictate a relevant and meaningful result from theperspective of the source, based upon criteria of user profiles,weighted definitions, and based upon user defined input values. Thisbenefits authors or advertisers who desire input from a targeted usersource with specific weighting characteristics and/or profiles.

The system, in some embodiments, enables the results of the data(collected, managed and stored by the system) collected by a methodutilizing the processing and management algorithms of the business rulesand data processing manager (BRDPM), for display by the system for thebenefit of future users and user groups.

The system, in some embodiments, enables subsequent users and usergroups to search, view, compare, contrast and have access to theweighted parameters, formulas, and/or rules set. Subsequent users willhave the option to further provide and contribute input about theparameters, formulas and/or rules set via the data input task scheduler.Such input will be collected by the server and will be added to thestored data based using a weighted and predefined formula provided bythe initial user(s) or user group(s) managed by the system and thebusiness rules and data processing manager. In some examples, the user(or UGA) may require future user to provide data (e.g., profileinformation or e-mail address) to gain access to system and system data.

The system, in some embodiments, includes a method wherein a user canremotely (via a communications network), provide volunteered dataspecific to the values, score, or relevancy to each previously definedparameter(s) or data field(s) specific to a particular subject matter.The inputted data from the user will be collected by the Data InputManager and will be added and combined with data provided by other usersby the System. Inputted data will be managed by the business rules anddata processing manager and will be stored in the database according tothe weighted and predefined formulas provided by the initial user(s) oruser group(s).

The system, in some embodiments, incorporates a method of wherein a usercan remotely provide and input specific and volunteered profileinformation about him/herself directly into the User Profile Manager andDatabase for purposes of validation. User profile information will bestored in the database for the benefit of providing and enhancing theweighted, relevant and meaningful content of the specific parameters anddata fields of all collected data for the benefit of the user andsubsequent users and user groups. Further validation of the user enablesthe user greater access to data and uAffect modules to contributefeedback, scores, ratings and other user input.

The system, in some embodiments, includes a method wherein the user oruser group can predefine the formula that defines the extent of theweightings specific to the collected user profile information and definethe rules that influence and contributes (or contrasts) to theparameters of the specific data set to be collected by the rule base andquality engine (RBQE) and processed by the business rules and dataprocessing manager. User profile information will contribute to theformulas (predefined by the user or user groups) of determiningmeaningful feedback for subsequent and future users and the display ofthe cumulative results of inputted data.

The system, in some embodiments, incorporates a method wherein thepreviously defined parameters and data fields of a specific subject aredisplayed by the system's data output content and symbol engine tosubsequent users. Data input from the subsequent users from theparameters and data fields of a specific subject, are then collected bythe system via the communication network, and managed by the businessrules and data processing manager. The data output content and symbolengine (DOCSE) assigns values to the resulting cumulative and weighteddata based upon the users' predefined rules set that includes weighting,rules, scoring and storing the data in the database.

The system, in some embodiments, includes a method where in the storedinputted, data form the users is organized and managed to display thecumulative results of the stored data. Results are processed by theoutput content and symbol engine based upon previously user-definedparameters that detail the weight and influence of each data fieldcollected and how the data is then to be reflected in the final result.A single or multivariate score, symbol or marker is the end result thatis displayed by the system for the benefit of future users.

The system, in some embodiments, includes a method wherein those userswho have provided user profile information, can benefit from optimizedsearch results when the user profile manager incorporates the userprofile information and weightings priority ranking of the user definedparameters, enhancing the meaningful search result generated by the dataoutput content and symbol engine. The users profile information isprocessed by the business rules and data processing manager thatprovides the previously defined weighted formula, to the data outputcontent and symbol engine. The output content and symbol engine (OCSM)gathers the stored data sets from the database provided by previoususers (including or excluding users with similar profile information)about a specific topic, parameter or subject, combines this informationwith the user profile information and process the information fordisplay to the user as a customized, weighted, resulting score (or asymbol or marker) specific for the user. The benefit of one applicationis a result that is displayed to the user that is the cumulative, and/orweighted, result from other users with similar user profiles.

The system, in some embodiments, includes a method where data from thesystem can be remotely accessible to a user who can search, compare orcontrast and have displayed a meaningful and relevant result. The resultbeing a set of data comprising of feedback from the user specified groupthat is stored in a database according to predefined data formulasmanaged by the rule base and quality engine (RBQE) and the businessrules and data processing manager (BRDPM). Feedback data from previoususers stored in the database, is collected and displayed for the user.Data displayed includes the separate parameters or data fields about aspecific subject of inquiry, and the weighted, combined, collectedinputted data, or the values or scores, of each parameter or data field.

One embodiment of the system includes a method of wherein the outputcontent and symbol engine (OCSE) displays the univariate or multivariatedata from each parameter from the feedback (inputted data) and values orscores provided by the users collectively. Feedback typically comprisingof two or more parameters with each parameter having different combinedvalues or scores to generate a consolidated symbol or marker defined bythe authors of the data and/or the user(s) and/or user groups.

One embodiment of the system uses a method wherein the output valuesfrom each parameter can be summarized and incorporated into the form ofa proprietary symbol or other easily recognizable markers such as faces,colors, graphs, lines in any combination incorporating numbers andletters and/or with any type of motion including flashing or text toaudio conversion. This method provides a result that is created andmanaged by the data output content and symbol engine (DOSE) managed bythe business rules and data processing manager. Combining the output ofmultivariate values into a symbol or other summarized marker, benefitssubsequent users by displaying a multivariate result that summarizesmeaningful content that is weighted and customized to the searchinguser.

One embodiment of the system incorporates a method wherein the outputsymbol comprises the parameter/value output compilation and thecumulative weighted results summary data of each parameter into a symbolor combination of symbols that display the value results of each of theparameters according to the formula provided by either one user or auser group, or a formula that is the weighted, cumulative result of auser or a user group. This information is collected, stored and managedby the business rules and data processing manager (BRDPM). This methodincorporates a resulting output symbol that is dynamically hot-linked todisplay the details of the parameter/value output compilation and thecumulative weighted results summary page generated by system's dataoutput content and symbol engine. A user can click on the symbol ormarker described in this example and can access the specific parametersof the stored data set (feedback from other users) and the cumulative,and/or weighted, values of each parameter.

One embodiment of the system utilizes a method enabling the system togenerate custom and weighted search results and to have the resultsdisplayed as a corresponding symbol or marker with a unique andconsistent look in list form defined by the user and/or the user group.Parameters predefined by the user and/or the user groups is displayednext to corresponding search results from a search engine, generated bythe business rules and data processing manager and the data outputcontent and symbol engine (DOSE).

One embodiment of the system incorporates a method wherein a user can benotified of resulting weighted scores or search results via notificationoptions that have been predefined by a user, administrator or a usergroup. Notification can be via e-mail, wireless mobile, RFID, webpage,blog (i.e., a web log on the internet) or other computer audio/visualaids. Some embodiments of this method include notification options withthe ability to easily access and view the parameter/value outputcompilation and the cumulative weighted results summary page generatedby systems' data output content and symbol engine and the user profilemanager.

One embodiment of the system incorporates the method where a monetarycharging mechanism is operative, based on the request to access data, tocharge an access fee or a subscription, to access the data and/or postdata managed by the administrative module and the business rules anddata processing manager of the system.

One embodiment of the system uses a method wherein a user or user groupthat is an author, manufacturer, promoter or any other entity withcommercial interest, can solicit feedback from the users by providingdata fields and defining parameters and topics for meaningful feedbackinterfacing. Relevant feedback is collected in the form of questions,comments or other meaningful feedback, during the method and process andmanaged by the administrative module within the system and provided bythe data input task scheduler, and the data input manager.

One embodiment of the system utilizes a method of wherein a user(s) canprovide solicited and unsolicited feedback that automatically integratesthe user's profile information and the user's weightings of parametersand other user input data, to another user, user group, author,manufacturer, promoter or other commercial interest using the systemwith assistance from the data input manager of the system.

One embodiment of the system uses a method using the system in such afashion wherein the business rules and data processing manager uses aplurality of tools to analyze the user provided feedback and attempts tofind relationships with the user-centric and user-defined input dataincluding historical trends, prediction analysis, and other economic andstatistical modeling tools.

One embodiment of the system utilizes a method that incorporatesstatistical analysis tools including (but not limited to) regressionanalysis, general linear model, principal components analysis, lineardiscriminant analysis, discriminant function or canonical-variateanalysis, logistic regression, multivariate analysis of variance,artificial neural networks, multidimensional scaling, canonicalcorrelation analysis managed by the administrative module and thebusiness rules and data processing manager.

One embodiment of the system uses a method that can employ tools formomentum analysis (MA) utilizing the system and the database of userinputted data. Evaluation of user profiles, user defined factors, userdefined weightings of the parameters and variables, coefficients,principals, characteristics, formulas and correlations combined withother information including micro and macro data such as overall markettrends, will further define momentum analysis to characterize momentumtheory, momentum behavior and momentum predictions of users, user groupsand defined entities. Momentum analysis is utilized for organizing dataincluding market, user, product or service status trends. The data isthen compiled with user-centric definitions, organized and stored basedupon predetermined user or user group parameters, for the purpose ofdisplaying the results in summary and multivariate symbol format usingthe parameter/value output compilation and the cumulative weightedresults summary, generated by the data output content and symbol enginewithin the System.

One embodiment of the system uses a method that formulates a userdefined (or user group defined) cumulative, and/or weighted,user-centric prediction result(s) generated and displayed by a summarysymbol(s) based upon predefined parameters, managed by the systemcomponents described above.

In some embodiments, the present invention provides an apparatus thatincludes a computer server, wherein the computer server iscommunicatively coupled to a plurality of clients over thecommunications network, and wherein the server includes: a data inputdevice configured to elicit and receive input data from the plurality ofclients, wherein the input data includes both a user profile thatincludes user-selected relevancy weights for each of a plurality of((parameters)), and user ((ranking data associated with each of aplurality of entities)); a classifier that classifies each user into aplurality of usergroups selected from a superset of usergroups based onthe user profile of that respective user; a database configured to storethe ranking data in a manner that retains a separation of ranking dataof different usergroups; and an output device that gathers data from thedatabase and presents refined data to the user based on relevancyweights from the user's profile.

In other embodiments, each usergroup can be considered a group or anassociation of which the user is a member. For example, a usergroupcould include just a single user (in some embodiments, each user forms ausergroup of just that single user). A user is typically a member of aplurality of usergroups, for example, a user could be a member ofusergroup “musicians”, usergroup “men” (male or female), usergroup“married” (or single, widowed or divorced), usergroup “30-somethingyears old”, usergroup “operating system preference” (e.g., PC orMacintosh), usergroup “economic class” (e.g., poor, middle class, orwealthy), usergroup “video game player”, usergroup “buying preferences”(e.g., internet or brick-and-mortar, or cash vs. credit card), usergroup“daylily grower”, usergroup “member of the Sadler family”, and the like.

In some embodiments, the usergroups can also be overall preferences,such as entertainment: usergroup “clean-humor preference of comedians”,or usergroup “accepts comedian who use innuendo” or usergroup “insultingand put-down comedians”; products: usergroup “film cameras”, usergroup“point-and-shoot digital cameras”, or usergroup “high-functionsingle-lens reflex (SLR) digital cameras”. Other classifications caninclude eating, traveling, durable goods.

In some embodiments of the apparatus, each of a plurality of users isautomatically a member of a single-user usergroup for just that user.This allows the system to handle individual users as one type ofusergroup, rather than separate classifications.

In some embodiments of the apparatus, each of a plurality of users candefine additional usergroups to be added to the superset of usergroups.In contrast, conventional systems have limited ability to defineadditional usergroups.

In some embodiments of the apparatus, each of a plurality of users canclassify that respective user into a usergroup that was notautomatically selected by the classifier.

In some embodiments of the apparatus, each of a plurality of users canremove that respective user from a usergroup that was automaticallyselected by the classifier.

In some embodiments of the apparatus, each of a plurality of users canadjust relevancy weights of ranking data based on which of a pluralityof user-selected usergroups the ranking data came from.

In some embodiments of the apparatus, each of a plurality of users canadjust relevancy weights of ranking data based on an age {{time elementor parameter}} of the ranking data.

In some embodiments of the apparatus, each of a plurality of users canadjust relevancy weights of ranking data based on a plurality ofuser-defined distances within a parameter space.

In some embodiments of the apparatus, each of a plurality of users canadjust relevancy weights of ranking data based on a plurality ofdistances within a user-defined parameter space.

In some embodiments of the apparatus, each of a plurality of users canadjust relevancy weights of ranking data based on a context of theproposed use of the relevancy-weighting ranking.

In some embodiments, the present invention provides a method implementedat least in part in a computer server, wherein the computer server iscommunicatively coupled to a plurality of clients over thecommunications network. This method includes eliciting and receivinginput data from the plurality of clients, wherein the input dataincludes both a user profile that includes user-selected relevancyweights for each of a plurality of ((parameters)), and user ((rankingdata associated with each of a plurality of entities)); initiallyclassifying each user into a plurality of usergroups selected from asuperset of usergroups based on the user profile of that respectiveuser; storing the ranking data into a database in a manner that retainsa separation of ranking data of different usergroups; and gathering datafrom the database and presenting refined data to the user based onrelevancy weights from the user's profile.

In some embodiments of the method, the classifying includes classifyingeach of a plurality of users as a member of a single-user usergroup forjust that user.

Some embodiments of the method further include eliciting and receivingusergroup-definition; and defining additional usergroups to be added tothe superset of usergroups.

Some embodiments of the method further include eliciting and receivingusergroup-classification data from a user; and further classifying thatrespective user into a usergroup that was not automatically selected bythe initially classifying.

Some embodiments of the method further include eliciting and receivingusergroup-declassification data from a user; and removing thatrespective user from a usergroup that was automatically selected by theinitially classifying.

Some embodiments of the method further include eliciting and receivingrelevancy-weight data from a user; and adjusting relevancy weights ofranking data based on which of a plurality of user-selected usergroupsthe ranking data came from.

Some embodiments of the method further include eliciting and receivingrelevancy-weight data from a user; and adjusting relevancy weights ofranking data based on an age {{time element or parameter}} of theranking data.

Some embodiments of the method further include eliciting and receivingrelevancy-weight data from a user; and adjusting relevancy weights ofranking data based on a plurality of user-defined distances within aparameter space.

Some embodiments of the method further include eliciting and receivingrelevancy-weight data from a user; and adjusting relevancy weights ofranking data based on a plurality of distances within a user-definedparameter space.

Some embodiments of the method further include eliciting and receivingrelevancy-weight data from a user; and adjusting relevancy weights ofranking data based on a context of the proposed use of therelevancy-weighting ranking.

Some embodiments of the invention include an apparatus that includes: acomputer server configured to gather data from a plurality of sourcesfor compilation into at least one searchable database that is accessiblethrough a communications network, wherein the computer server iscommunicatively coupled to a plurality of clients over thecommunications network, and wherein the server includes: a data inputdevice configured to elicit and receive input data from the plurality ofclients, wherein the input data includes both a user profile thatincludes relevancy weights for each of a plurality of ((parameters)),and user ((ranking data associated with each of a plurality ofentities)); a database configured to store the input data in a mannerthat retains an identification of a particular user associated with eachof a plurality of the stored ranking data and/or weighting data; and anoutput device that gathers data from the database and presents refineddata to the user based on the user's profile.

Some embodiments further include a data output content device (DOCD)(and/or a display manager).

Some embodiments further include a profile-management device

In some embodiments, the present invention provides an apparatus thatincludes a computer server, wherein the computer server iscommunicatively coupled to a plurality of clients over thecommunications network. The server further includes a source ofsearch-engine-result data (i.e., hyperlinks); a relevancy engine/program(PAMC) that analyzes source data indexed by the search-engine-resultdata for relevance to a selected user, wherein the relevancy engine'sanalysis is at least in part based on a plurality of relevancyparameters, yields a multivariate analysis result; [also include groupcharacteristics] an output engine (DOCSAM) that transmits themultivariate analysis result to the specified user.

In some embodiments, the relevancy engine/program is configured toreceive from the selected user additional parameters to be analyzed bythe relevancy engine/program.

Some embodiments further include a presentation engine that receives themultivariate analysis result and presents to the specified user aplurality of multivariate icons selected based on the multivariateanalysis result.

In some embodiments, the relevancy engine/program includes agraphical-user interface that elicits and receives a further inquiryfrom the selected user to obtain a list of the relevancy parametersassociated with one of the plurality of multivariate icons andrespective relevancy-interpretation rules associated with each of thelisted relevancy parameters. In some such embodiments, therelevancy-interpretation rules include weightings for each one of aplurality of the relevancy parameters individually. In otherembodiments, the relevancy-interpretation rules include combinatoricrelevancy rules (CRR) susceptible of combinatoric analysis (CA) by therelevancy engine of at least one combination of a plurality of therelevancy parameters. In some embodiments, the apparatus includes agraphical-user interface that elicits and receives input data from theselected user to define or modify at least one of the combinatoricrules.

As used herein, combinitoricals are combinatoric relevancy rules,combinatorics, algorithms, metadata (i.e., data about other data) and/orthe like that are used or usable (beyond simple individual weightings)to provide a relevancy result based on a plurality of relevancyparameters.

As used herein, MUFT are relevancy parameters that include one or moreof modes, utilities, functions and topics (MUFT).

As used herein, relevancy factors include one or more of parameters,values, algorithms, combinatorics, and classifications. In someembodiments, each of a plurality of the relevancy factors include a timeparameter associated with a search comparison or data analysis query.

In some embodiments, individual users input data that define additionalrelevancy factors and modify existing relevancy factors. In someembodiments, user group input is used to define additional relevancyfactors and modify existing relevancy factors.

In some embodiments, the present invention is applied to adating-program (and/or social networking) system, and allows individualusers and groups of users to define and modify relevancy factors used toanalyze interpersonal compatibility and or suggest hookups. In someembodiments, the system allows individual users to define relevancyfactors, apply these to a search for a compatibly person or group ofpersons, and to contact one or more persons through the system based onrelevancy analysis results.

The present invention provides a user-centric approach for users tocreate and/or join user groups, wherein each user group is associated(in the computer) with a default user-group set of relevance factors. Insome embodiments, each default user-group set of relevance factors iscorrelated to a user-specific set of data (e.g., based on answersprovided to the system by a specific user. The user-group set ofrelevance factors can then be examined by each user, and modified byadditional preferences of that user to obtain a user-specific-modifieduser-group set of relevance factors. In some embodiments, theuser-specific-modified user-group set of relevance factors can be usedin a feedback manner to update/modify the default user-group set ofrelevance factors (e.g., by adding additional factors to the defaultuser-group set of relevance factors or by modifying existing factors).In some embodiments, user-specific-modifications to a user-group set ofrelevance factors is collected and aggregated into the defaultuser-group set of relevance factors.

In some embodiments, a new user group is definable by user input,wherein the new user group is associated with an initial user-group setof relevance factors. Over time and use, the initial user-group set ofrelevance factors, initially presented to additional users, is modifiedover time to provide a dynamically updated default user-group set ofrelevance factors. For example, a movie-enthusiast user group can becreated by one or more users, and the initial user-group set ofrelevance factors could include only the movie industries rating systemof G, PG, PG13, R and X, for example. This overly simplistic set ofrelevancy factors are inadequate for a movie-enthusiast user group, whothen add additional relevancy factors, such as nudity, language,violence and the like. Other users could add parameters such as genre(westerns, romance, comedy, musicals and the like). Over time, a largenumber of relevancy factors (which are input to the system) are obtainedthat are important in one way or another to a wide variety of movieenthusiasts. Each movie is rated by the various members of themovie-enthusiast user group according to the various relevancy factorsthat have been added over time.

Movie-Enthusiast Example

Some users could then define subgroups or spin-off groups that have aninterest in one specific genre of film, or a type of media, or aparticular director or actress. These spin-off user groups could bestarted using the default user-group set of relevance factors from themovie-enthusiast user group, but that spin-off group's set of relevancefactors would then evolve over time in a manner that is distinct anddifferent from the default user-group set of relevance factors of thegeneric movie-enthusiast user group. For example, in some embodiments,the present invention provides a computerized method that includesdefining a first user group (e.g., movie-enthusiast user group) thatincludes a plurality of users (e.g., its initial set of users);providing a first default user-group set of relevance factors (e.g., themovie industries rating system of G, PG, PG13, R and X) and associatingthe first default user-group set of relevance factors (G, PG, PG13, Rand X) with the first user group (the movie-enthusiast user group);defining a second user group (e.g., persons who enjoy satire); derivingan second default user-group set of relevance factors based from thefirst default user-group set of relevance factors (e.g., starting with(G, PG, PG13, R and X)) and associating the second default user-groupset of relevance factors with the second user group (i.e., the satiremovie enthusiasts user group); modifying the first default user-groupset of relevance factors; and modifying the second default user-groupset of relevance factors (e.g., by adding a parameter that rates theamount of satire) in a manner different than the modifying of the firstdefault user-group set of relevance factors (e.g., by adding a parameterthat rates the amount of violence). Over time, other relevancy factorscould be added to either to all movie-enthusiast user groups (e.g.,whether each rated movie is available on a HD DVD, which may be ofinterest to all) or to a specified subset (e.g., the amount of darkhumor or offensive satire, which could be more applicable to the satiremovie-enthusiast user group). In some embodiments, the additionalrelevancy factors are fed back into one or more (e.g., a selectedplurality of) the user-group sets of relevance factors.

Additional Examples of Some Embodiments of the Invention

Individuals choose to relocate for many different reasons. Choosing anew local can be very intimidating and frustrating. Trying to find thebest place to live to fit your lifestyle can be overwhelming. Someindividuals use third party media endorsements such as magazine rankingsor news print ranking as a guide in their decision making process.Unfortunately media editors and others use criteria and weighting offactors for choosing a good place to live that can be much differentthan individual's relocation criteria. For example in “Money” magazinesannual rankings of the best place to live, “weather” is a majorweighting factor. Traditionally, northern Midwest plain cities arescored negatively because of their cold winters. For some individualsattempting to relocate, they may like the cold. Because “Money” magazineranks Midwest plain cities lower due to the cold, this individual wouldview “Money” magazines rankings as inaccurate. In another example othermedia sources have ranked Rochester Minn. as one of the best places inAmerica to live because of it's proximity to the Mayo Clinic, because ofit's excellent elementary school system, number of advanced degreeprofessionals per the population, a great park system and is extremelysafe from violent crime. On the surface if an individual was looking fora city to relocate to, Rochester Minn. would be an excellent choice. Ifyou are an individual that has children, have health problems, or wantto work in a health care environment with extremely educated individualsyou might have found the right place to live. But Rochester Minn. is afamily friendly town, no “Gentleman's Clubs”, limited nightlife, andwhat some would say is extremely boring for singles and young adults. InRochester over a third of its workforce works at the Mayo Clinic ahealth care facility. If the individual looking to relocate happened notto be interested in the Healthcare or related fields he or she wouldhave been misled by Rochester's ranking as a best place to live inAmerica, and may have relocated to an area not conducive to hislifestyle.

For the above example, the system would elicit input from users who livein, have lived in, visited, researched and evaluated Rochester. Theindividual choosing to relocate would list the parameters that theydeemed to be important tailored to their specific relocationrequirements. In the example above if a person used the invention andput in as their weighted parameters “Low Crime”, “Elementary education”,“Recreation” and “Healthcare Industry” then Rochester would come up as atop place to live in America. If the individual put in as their weightedparameters as, “Night Life”, “Manufacturing”, “Secondary Education” and“Single Life” Rochester Minn. would fall further down one's own personalweighted ranking list.

The invention will also help individuals who travel for business,recreation, or as tourists. One of the biggest problems with travelingis not knowing the restaurants or best tourist locations to visit. Oneof the most used modes of restaurant selection for an individual in anunfamiliar city is to ask the bellman at the hotel. Obviously bellmenrecommend restaurants that they are familiar with or at worst being paidto recommend. These two facts alone make your selection of a restaurantin a new city risky.

In one embodiment, the system will analyze input from past patrons, andreviewers of selected restaurants and analyze and store the inputteddata. The system will allow an individual to weigh the parameters thatare most important to the patron and give them recommendations throughany notification media such as cell phone, computer, and fax etc. Thesystem would also allow restaurants to log on to the system and searchas their weighted customer parameters to come up with potentialcustomers that fit the selected weighted criteria. If a certainrestaurant was going to have a special on prime rib for the weekend itcould target those individuals that are prime rib connoisseurs.Restaurants could use the system to target customers directly using cellphone, computers and other media devices.

For example an individual visiting Chicago logs on to invention andenters in their personal weighted parameters, such as “Chicago”,“Chinese Cuisine”, “Casual attire”, “Meal Price range $15-$25”, “FullBar”. The system will take the individuals user defined weighted andselected parameters analyze imputed data from other past patrons andprovide a personalized weighted relevancy list (1X, 2Y, 3Z, . . . ). Ifindividual would have put “Location from Spot” as the first weightedparameter then the personalized weighted relevancy list may have changedto (1Z, 2X, . . . 15Y). Modifying the parameter after the initialpersonalized relevancy list may eliminate potential restaurants as idealselections for a meal thus making choosing less risky.

Tourists or recreation travelers often face the challenges choosing thebest sites to visit. Chambers of Commerce and tourist centers often areinundated with solicitations from tourist and usually funnel individualinto the most popular or most visited destinations. These may not be thedestinations that best fit the preferences of the individual seekingrecommendations. Some individuals may not want to walk very far; somemay prefer water attractions, or attractions that are kid friendly.

Our system will take information from individuals who have visitedselected tourist sites and have used our invention to enter theirweighted parameters and corresponding uEffect score, analyze it andcompile the data. The individual tourist seeking recommendations fortourist destinations would enter in the user defined weighted parametersand would receive through a media source a corresponding list of touristattractions tailored to their specific needs.

One example would be a person that logs on to our system through acomputer terminal and puts in their user defined weighted parameterssuch as “location within 20 miles”, “child friendly”, “free admittance”,and “water related”. Being weighted and selected by the user, theindividuals weighted relevancy list would comprise of destinationsspecifically tailored for the individual user that had “location” as thenumber one parameter, followed by “child Friendly” and so on until thelist was complete.

Websites, Chat rooms and Blogs have become increasingly hard tonavigate. When an individual types in a subject they are interested inhundreds if not hundreds of thousands of selections appear. The numberone choice on a particular search engine may be the most visitedWebsite, Chat room or Blog, but may not be the most relevant to theuser. Third party entities can influence rankings on selected searchengines by artificially inflating hits as an example in order to move upthe rankings. An individual may not have time to view hundreds orhundreds of thousands of particular Websites, Chat rooms or Blogs tofind the right fit. This is called “push internet”. As defined as athird party such as a search engine that has arranged selections basedon search engine criteria and listed the selections for the user.

In the invention the system would change the internet from a “pushinternet” to a “pull internet”, as defined as a user based system thatpulls the selections from the internet that the user defines as fittingtheir individual parameters and lists them according to personalweighted 1 preferences through a uEffect rating. A “pull internet” willsave individuals time, and make the internet a personalized tool in thedecision making process.

Today, a person looking for an internet site discussing the Presidentsjob approval rating would get a listing of over 200,000 hits. It wouldbe a daunting task to try to find the site matching the individualuser's preferences. The invention would elicit input from the readers ofthe 2000,000 sites and provide feedback through user weightedparameters. The system would then collect, analyze, compile and storethe individuals weighted parameters. This would allow a new user toselect and define her or his own weighted parameters to create anindividualized relevant list.

An example of the invention would have a user log onto a system andthrough a device enter their weighted parameters. A user may definetheir weighted parameters as, “accuracy”, “timeliness of information”,“democratic slants”, and “location Minnesota”. With the user definedparameters the “pull internet” would search, combine, analyze andcompile a list of sites for the user. The sites listed would then belisted according to the user defined weighted parameters. The list wouldexclude site that were “republican slanted”, “inaccurate” or sites thathave “outdated information” or not from the “location. Minnesota”.

When choosing to purchase a retail product either from a retail store,an internet store or on a auction site such as EBay individuals canbecome overwhelmed or confused by the different choices. An individualwith limited time may take an easy route and purchase the first observedor most conveniently located item. Advertisers overwhelm potentialcustomers with print, television, radio, and internet advertisingoffering the same items at different prices or different brands andqualities making choosing difficult. In addition to the advertisingconfusion trying to find a gift or purchase an item for anotherindividual not knowing an individuals personal preferences makesshopping for some individuals extremely time consuming, risky (someonemay not like the gift) and an overall less then desirable activity.

The present invention will change the way we shop. The system will helpindividuals save time when shopping, find the perfect item according totheir users and gift recipients personal parameters. The invention willalso make purchasing a gift for another person less time consuming andless risky. The system will also help retailers by allowing then todirectly target and advertise to individuals based on their purchaserequirements.

An example of how the system will help deciding what to purchase andwhere to purchase starts with the individual logging on to the systemand entering the user weighted parameters. If a person is looking topurchase a new television a user may enter weighted parameters such as“Made in the United States”, “High Definition”, “37 Inch or smaller”,and “Price under $200.00”. The system will then take the users weightedparameters search the system for the list of televisions on any type ofmedia device such as a cell phone, fax, computer, Etc. that fit theusers weighted parameters. In this example the user may change theweighted parameters, in order to compare different options such asmaking the weighted parameters “High Definition”, “37 Inch or Smaller”and “Price under $200”. This quarry and search would allow a user tocompare United States-made High-Definition, 37-inch televisions pricedunder $200.00 to all High-Definition, 37-inch televisions under $200.00made anywhere in the world. The user has the ability to shop for theitems that meet his exact purchase requirements at the best availableprice.

Taking the previous example one step further, if a user has questionsregarding the product to purchase, the individual may log onto thesystem and elicit and enter in weighted profile parameters such as“Male”, “Age 25-40”, “Sports Fan”, and “Televisions”. This would allowthe user to connect with an individual to receive feedback back from auser group that matches his weighted profile parameters. In this exampledata collected, compiled, and analyzed from a user group that matchesthe individuals weighted profile parameters would then be transmitted tothe user. The suggestion of a certain type of television such as a HighDefinition, 42 Inch, flat-screen would be displayed to the user. Whatmakes the system powerful is the suggestion would come from a user groupthat exactly matches the user's profile of Males, age 25-40 who is asports fan. This input from a user group would help reduce poorpurchases. Once the user was able to define through user groupsuggestions on a television that would match his weighted profileparameters, he could then use the system as explained above and put inthe weighted parameters such as “High definition”, “42 Inch”, “FlatScreen” and what ever additional parameters to get the best televisionthat matches his purchase parameters.

The present invention outlines a system and method that can provideusers, and groups of users, with an apparatus that can provide morerelevant and meaningful search, comparison and data analysis. The systemis a user-centric system that elicits and receives user data thatenables the users, and the user group or association as a whole, toinput data and define the elements that are relevant to searching,comparing or analyzing a topic, product, service, article, event,person, place or any other user defined topic.

Users and user groups can define the rules and algorithms that mine thestored feedback data, and can dynamically manipulate the searchparameters, the weightings of the parameters and other filters or tuningmechanisms.

Cumulative summary scores can be displayed by the system in a systemsuggested or a user (or user group) defined process. Users (and usergroup associations) can further define the access levels within thesystem to access stored data. Data can be tracked, stored and displayedwithin the system that enables users to track trends, perform predictionanalysis and define momentum quotients.

In some embodiments, the present invention provides a computer server,wherein the computer server is communicatively coupled to a plurality ofclients over the communications network, and wherein the serverincludes: a source of search-engine-result pointers; optionally a sourceof internally stored data on a database; a relevancy-and-comparisonengine (RACE) program that analyzes, for relevance to a selected user,source data indexed by the search-engine-result pointers, wherein theRACE program's analysis is at least in part based on a plurality ofrelevancy factors, and yields a multivariate analysis result; an outputengine (DOCSAM) that transmits the multivariate analysis result to thespecified user. Some embodiments further include a database connected tothe relevancy engine/program and configured to be searched and to returnpointers to the database's internal data.

In some embodiments, the relevancy factors includes a time parameter foreach of a plurality of MUFT (modes, utilities, functions and topics),and the RACE engine generates a momentum quotient (MQ) (e.g., trendanalysis of the plurality of relevancy parameters).

In some embodiments, the relevancy factors includes the combinitoricalcharacteristics of the MUFT parameters resulting is a list or graphicaldisplay of the momentum combinatoric analysis (MCA).

In some embodiments, the relevancy-and-comparison engine (RACE) programperforms a grammar and/or syntax-based analysis of the source dataindexed by the search-engine-result pointers to obtain results for auser-specified relevancy factor.

In some embodiments, the apparatus a relevancy-and-comparison engine(RACE) program that performs a context-sensitive analysis of the sourcedata indexed by the search-engine-result pointers to obtain results fora user-specified relevancy factor. The relevancy engine/program can beconfigured to receive from the selected user additional parameters to beanalyzed by the relevancy engine/program.

In some embodiments, a presentation engine receives the multivariateanalysis result and presents to the specified user a plurality ofmultivariate icons selected based on the multivariate analysis result.In one example, the relevancy engine/program includes a dynamicgraphical-user interface that elicits and receives a further inquiryfrom the selected user to obtain a list of the relevancy parametersassociated with one of the plurality of multivariate icons andrespective relevancy-interpretation rules associated with each of thelisted relevancy parameters.

In some embodiments, the relevancy-interpretation rules includeweightings for each one of a plurality of the relevancy parametersindividually. In another example of the invention, therelevancy-interpretation rules include combinitoricals usable for acombinatoric analysis of at least one combination of a plurality of therelevancy parameters.

In some embodiments, the apparatus includes a graphical-user interfacethat elicits and receives input data from the selected user to define ormodify at least one of the combinitoricals. The system and apparatus canbe configured wherein at least one of the combinitoricals is based onone or more group characteristics.

In some embodiments, at least one of the combinitoricals is based on oneor more group characteristics, wherein the selected user specifies agroup from which to obtain the group characteristics.

In some embodiments, at least one of the combinitoricals is based on oneor more group characteristics, wherein the selected user indirectlyspecifies a group by providing self-characterizing answers.

In some embodiments, the invention includes at least one of therelevancy parameters as a user-specified parameter to cause the analysisto be from a perspective of someone other than the user (e.g., a memberof a group that does not include the user, the ability to influence therelevant search mechanism to be targeted for a person other than thespecified user (different user—e.g., boy's night out vs. date withwoman)).

In some embodiments, at least one of the relevancy parameters is a useand/or a utility mode for which the returned data is to be applied (theability to specify a situation and/or add a situation and/or useparameter for the analysis (different uses for the restaurant e.g.,boy's night out vs. date with woman)).

In some embodiments, the apparatus includes a database (e.g., aninternal database having cached data (a local copy of data fromelsewhere)) connected to the relevancy engine/program and configured tobe searched and to return pointers to its internal (local copy) data.

In some embodiments, the internal data includes review informationobtained from one or more users, wherein the review information includesuser and user group defined rules, formulas and algorithms for dataaccess, storage, display and search tuning and modifications to enabledata analysis.

In some embodiments, the apparatus utilizes the internal data andincludes review information obtained from one or more users, wherein thereview information includes empirical, implies, implicit and explicitfeedback (votes, ratings, scores, weights).

In some embodiments, the present invention provides an apparatus thatincludes a computer server, wherein the computer server iscommunicatively coupled to a plurality of clients over thecommunications network, and wherein the server includes: a data inputdevice configured to elicit and receive input data from the plurality ofclients, wherein the input data includes both a user profile thatincludes user-specific attributes of the user and user-selectedrelevancy weights for each of a plurality of ((parameters), wherein theuser defines and adds to the data being analyzed for relevance at leastone of the parameters), and user ((ranking and/or scoring dataassociated with each of a plurality of entities)); a classifier thatclassifies each user into a plurality of usergroups selected from asuperset of usergroups based on the user profile of that respectiveuser; a classifier that generates a momentum classification (MC)combining users into a plurality of user groups selected from a supersetof usergroups; a classifier that generates a momentum parameterclassification (MPC) combining user and usergroup parameters, MUFT,rules and algorithms into a plurality of usergroups from a superset ofusergroups or associations; a database configured to store the rankingdata in a manner that retains a separation of ranking data of differentusergroups; and an output device that gathers data from the database andpresents refined data to the user based on relevancy weights, definedparameters, MUFT, rules and/or algorithms, from the user's profile.

In some embodiments, each of a plurality of users is automatically amember of a single-user usergroup for just that user. In anotherembodiment, each of a plurality of users can define additionalusergroups to be added to the superset of usergroups. In anotherexample, each of a plurality of users can classify or remove thatrespective user into a usergroup that was not automatically selected bythe classifier.

In some embodiments, a user can identify other users (based uponcriteria defined by the user) to communicate and solicit feedback fromother users directly via a forum provided by the system creating asocial interface between users based upon criteria defined by the usersthemselves.

In some embodiments, an output device generates a data point (includinga topic, parameter, factor or other information) or an iconic summaryrepresentation of a ranking based on. In another example, the data thesystem and apparatus independently collects and processes (with theuser's predefined preferences, profiles and definitions) creates apredictive, suggested data point to the user.

In some embodiments, a plurality of parameters for each of a pluralityof attributes of the resulting iconic representation(s) is based upondefined user group preferences or based upon the preferences provided bythe user. In another example, each of a plurality of users can adjust,filter and tune the relevancy weights of ranking data based on datapoints, parameters, MUFT, governing rules, algorithms, of the rankingdata. User profiles, other parameters or factors of the ranking data canalso be incorporated.

In some embodiments, the search and analysis function is furtherfiltered and tuned to correlate with suggested or selected user profileinformation.

In some embodiments, the system provides a method for eliciting andreceiving input data from the plurality of clients, wherein the inputdata includes both a user profile that includes user-selected relevancyweights for each of a plurality of parameters, and user ranking dataassociated with each of a plurality of entities is incorporated. Thiscan also include:

-   -   a) a means for initially classifying each user into a plurality        of user groups selected from a superset of user groups based on        the user profile of that respective user;    -   b) a means for storing the ranking data into a database in a        manner that retains a separation of ranking data of different        usergroups; and    -   c) a means for gathering data from the database and for        presenting refined data to the user based on relevancy weights        from the user's profile.

In some embodiments, the apparatus contains the means for classifyingincluding a means for classifying each of a plurality of users as amember of a single-user usergroup for just that user. This example caninclude a means for eliciting and receiving usergroup-definition; ameans for defining additional usergroups to be added to the superset ofusergroups, a means for eliciting and receiving usergroup-classificationdata from a user; and a means for further classifying that respectiveuser into a usergroup that was not automatically selected by theinitially classifying.

In some embodiments, the system includes a means for eliciting andreceiving usergroup-declassification data from a user; and a means forremoving that respective user from a usergroup that was automaticallyselected by the initially classifying.

In yet another embodiments, the system includes a means for elicitingand receiving relevancy-weight data, and rules and algorithms supportingthe data from a user; and a means for adjusting relevancy weights ofranking data based on which of a plurality of user-selected usergroupsthe ranking data came from.

In some embodiments of the invention, the method provides a means fordata gathered from the users to be processed algorithmically based uponuser definitions to generate a momentum query (MQY) to suggest topics,parameters and factors, present data and feedback and provide analysisand queries. Such a function enables the system to generate a momentumprediction (MP) to predict meaningful and relevant tending data tosupport the identification of relevant topics and parameters foreconomical modeling, statistical analysis, momentum analysis (MA), anddetermining the MQ.

In some embodiments, the system provides for a method of receiving aplurality of search-engine-result pointers (e.g., hyperlinks), fetchsource data pointed to by the search-engine-result pointers, retrievingdata stored on an internal data base, perform a relevancy and comparisonanalysis of the fetched source data for relevance to a selected user(wherein the analysis is at least in part based on a plurality ofrelevancy parameters, and outputting a multivariate analysis result) Thesystem provides for a means for transmitting the multivariate analysisresult to the specified user.

In some embodiments, the system provides a means for receiving from theselected user additional parameters to be analyzed by the relevancy andcomparison analysis. The method provided by the system can be configuredfor receiving the multivariate analysis result and presenting to thespecified user one or more dynamically linked icons selected from aplurality of multivariate icons based on the multivariate analysisresult.

In some embodiments, the relevancy and comparison analysis includesusing a graphical-user interface to elicit and receive a further inquiryfrom the selected user, and based on the further inquiry, obtain a listof the relevancy parameters associated with one of the plurality ofmultivariate icons and respective relevancy-interpretation rulesassociated with each of the listed relevancy parameters and presentingthe list to the user. In this example the relevancy-interpretation rulescan include weightings for each one of a plurality of the relevancyparameters individually.

In some embodiments, the relevancy-interpretation rules includecombinatoric algorithms for a combinatoric analysis of at least onecombination of a plurality of the relevancy parameters. An example ofthe system includes eliciting and receiving data, via a graphical-userinterface, from the selected user to define or modify at least one ofthe combinatoric rules.

In one example of the system, a computerized method comprises thefunction of defining a first user group that includes a plurality ofusers; defining a first user group association (UGA) that includes aplurality of users; providing a first default user-group set ofrelevance factors and associating the first default user-group set ofrelevance factors with the first user group; defining a second usergroup; deriving a UGA and correlating data points, parameters, rules,algorithms and profile information; deriving an second defaultuser-group set of relevance factors based from the first defaultuser-group set of relevance factors and associating the second defaultuser-group set of relevance factors with the second user group;modifying the first default user-group set of relevance factors; andmodifying the second default user-group set of relevance factors in amanner different than the modifying of the first default user-group setof relevance factors.

In some embodiments, the system incorporates a method to implement, atleast in part, a computer server, wherein the computer server iscommunicatively coupled to a plurality of clients over thecommunications network, the method comprising the functions of elicitingand receiving input data from the plurality of clients, wherein theinput data includes both a user profile that includes user-specificattributes about the user, and user ranking data associated with each ofa plurality of entities, initially classifying each user into aplurality of user groups selected from a superset of user groups basedon the user profile of that respective user; storing the ranking datainto a database in a manner that retains a separation of ranking data ofdifferent user groups; and gathering data from the database andpresenting refined data to the user based on relevancy weights,parameters, MUFT, rules and algorithms correlating to user's profile.

In some embodiments, the classifying includes classifying each of aplurality of users as a member of a single-user user group or UGA forjust that user. The system can provide a means for eliciting andreceiving usergroup-definition; and defining additional usergroups to beadded to the superset of usergroups. In addition, the system can performfunctions of eliciting and receiving usergroup-classification data froma user; and further classifying that respective user into a usergroup ora UGA that was not automatically selected by the initially classifying.

In some embodiments, the method includes eliciting and receivingusergroup-declassification data from a user; and removing thatrespective user from a usergroup that was automatically selected by theinitially classifying. In some examples, the system provides a means foreliciting and receiving relevancy weight data from a user; and foradjusting relevancy weights of ranking data based on which of aplurality of user-selected usergroups the ranking data came from.

In some embodiments, the user profile further includes user-selectedrelevancy weights for each of a plurality of parameters, MUFT, and therules and algorithms that apply to the stored data.

Some embodiments further include customizing a look-and-feel andusability of the user interface. For example, in some embodiments, thesorting interface includes user-defined organizational tools and iconswithin the dashboard that optimizes the relevancy of the searching,comparing or analyzing function that enable the user to drag and drop,right click or click and highlight to obtain a desired organization andre-organization of a function result.

{having the system suggest and predict results to a user as the userbegins a search or comparison} An apparatus of claim 15, and the methodof claim 8 wherein the apparatus provides a real-time and interactiveinterface with the systems' database and the inputted user profile,preferences and search and comparison criteria, to generate and displaydata that is suggested, predicted, prompted, previewed, weighted, andstored for the purposes of optimizing and tuning a users' search,comparison or analyzing function result.

In some embodiments, the system apparatus stores profile, historicaluser preferences and weighting data, in conjunction with other searchengines responses to optimize results. An apparatus utilizes a searchalgorithm that incorporates user profile information, user defined (andUGA defined) parameter priority rankings, and MUFT and parameterweightings to further tune and optimize the search results.

In some embodiments, the tuning, search, comparison and analysis of theabove is further tuned to incorporate scores, ratings, votes, or otherfeedback from external sources (e.g., other websites and DB).

In some embodiments, the security parameters incorporate user and UGAdefined methods and rules to manage users and user access to data tomitigate fraud.

It is to be understood that the above description is intended to beillustrative, and not restrictive. Although numerous characteristics andadvantages of various embodiments as described herein have been setforth in the foregoing description, together with details of thestructure and function of various embodiments, many other embodimentsand changes to details will be apparent to those of skill in the artupon reviewing the above description. The scope of the invention shouldbe, therefore, determined with reference to the appended claims, alongwith the full scope of equivalents to which such claims are entitled. Inthe appended claims, the terms “including” and “in which” are used asthe plain-English equivalents of the respective terms “comprising” and“wherein,” respectively. Moreover, the terms “first,” “second,” and“third,” etc., are used merely as labels, and are not intended to imposenumerical requirements on their objects.

What is claimed is:
 1. An apparatus comprising: a computer systemcomprising, a computer server, wherein the computer server iscommunicatively coupled to a plurality of clients over a communicationsnetwork, and wherein the computer server includes: a source of aplurality of search-engine-result pointers; a relevancy-and-comparisonengine (RACE) program stored on the server that, when the RACE programis executed, analyzes, for relevance to a first human-user, source dataindexed by the plurality of search-engine-result pointers, wherein theRACE program: elicits and receives, from the first human-user, aplurality of human-user-defined search terms; elicits and receives, fromthe first human user, a specification of a first group, wherein thefirst group is a self-identified set of human users, and wherein thefirst human user need not be a member of the specified first group,wherein the RACE program associates a first set of group-relevancyfactors with the group; elicits and receives, from the first human user,a plurality of human-user-defined relevancy factors, wherein theplurality of human-user-defined relevancy factors received from thefirst human user includes factors that are to be weighted by the RACEprogram to rank search-engine results for presentation to the firsthuman user in addition to the search terms received from the first humanuser; and wherein the RACE program's analysis is at least partiallybased on weights determined by the received plurality of the firsthuman-user-defined relevancy factors and the first set ofgroup-relevancy factors and wherein the received plurality of thehuman-user-defined relevancy factors for the first human user include alocation, and wherein the RACE analysis is based at least in part on thelocation.
 2. The apparatus of claim 1, wherein the computer systemutilizes momentum analysis to characterize momentum theory, momentumbehavior and momentum predictions of users, user groups and definedentities, by incorporating user-profile information, adding human-user(and user peer group) defined parameters, rules (algorithms) or metricsand human-user feedback including weighted criteria or parametersprovided by the human users, resulting in a momentum quotient.
 3. Theapparatus of claim 2, wherein the momentum quotient is at least in partbased on statistical analysis of source data indexed by the plurality ofsearch-engine-result pointers.
 4. The apparatus of claim 2, wherein themomentum quotient is at least in part based on statistical analysisusing a time parameter.
 5. The apparatus of claim 2, wherein relevantinformation includes information provided by other human users thatinclude users with similar profile information and ‘use’ of datacontext, and demanded data, feedback or information determined by thehuman users, a human usergroup, community or a peer group.
 6. Theapparatus of claim 1, wherein relevant information includes informationprovided by other human users that excludes users with similar profileinformation and ‘use’ of data context, and demanded data, feedback orinformation determined by the human users, a human usergroup, communityor a peer group.
 7. The apparatus of claim 1, wherein the computersystem is coupled to a plurality of clients over the communicationsnetwork; and includes search-engine-result data and analyzes source dataindexed by the search-engine-result data for relevance to a selecteduser group.
 8. The apparatus of claim 1, wherein the computer systemyields a multivariate-analysis result that includes human usergroupparameters and characteristics.
 9. The apparatus of claim 1, wherein theadministrator, as the first user, defines the relevant, weighted searchand comparison parameters.
 10. An apparatus comprising: a computersystem, that comprises a computer server communicatively coupled toclients over a wireless communications network, and wherein the serverincludes: a relevancy-and-comparison engine (RACE) program stored on theserver that, when the RACE program is executed, analyzes, for relevanceto a first human-user, source data indexed by the plurality ofsearch-engine-results, wherein the RACE program: elicits and receives,from the first human user, a plurality of human-user-defined searchterms; elicits and receives, from the first human user, a specificationof a first group, wherein the first group is a self-identified set ofhuman users, and wherein the first human user need not be a member ofthe specified first group, wherein the RACE program associates a firstset of group-relevancy factors with the first group; elicits andreceives, from the first human user, a plurality of human-user-definedrelevancy factors, wherein the plurality of human-user-defined relevancyfactors received from the first human user includes factors that are tobe weighted by the RACE program to rank search-engine results forpresentation to the first human user in addition to the search termsreceived from the first human user; and wherein the RACE program'sanalysis is at least in part based on weights determined by the receivedplurality of the first human-user-defined relevancy factors and thefirst set of group-relevancy factors.
 11. The apparatus of claim 10,wherein the computer server augments Internet searches, re-ranks searchresults, and provides recommendations for objects based on an initialsubject-matter query.
 12. The apparatus of claim 10, wherein thecomputer server elicits and receives user-volunteered profileInformation displayed and weighted with other users with similarprofiles, human-user-defined relevancy factors, interests, andassociations for purposes of social networking and gathering, feedbacksharing, and prediction and notification of future products, servicesand behaviors.
 13. The apparatus of claim 10, wherein human usersassociate with other human users who have a similar profile to enablesearches incorporating a social-interaction component, analyzeinterpersonal compatibility and provide the ability to contact one ormore human users through the system.
 14. The apparatus of claim 10,wherein human users associate with other human users in the first groupof users, and other users who have similar weightings of thehuman-user-defined relevancy factors, to have access to an associationpage wherein discussion forums are hosted by the apparatus facilitatinga user to post, chat and communicate with other individual users andpost comments to a discussion bulletin board, and wherein the apparatusfacilitates individual users, to define relevancy factors, apply theseto a search for a compatible person or group of persons, and to contactone or more persons in their home community based on relevancy-analysisresults.
 15. The apparatus of claim 10, wherein the computer systemsuggests and elicits topics; receives human-user-definedrelevancy-weight data from a human user or human user group; wherein theusers adjust relevancy weights of ranking data based on a context of theproposed use parameter of the relevancy-weighting ranking, and whereinthe social search aspects are facilitated and managed by the systembased upon rules and instructions predetermined by the user and the usergroups.
 16. The apparatus of claim 10, wherein the system facilitates aplurality of users, adjusting relevancy weights of ranking data based ona plurality of human user-selected-peer user groups from whom theranking data came, and wherein the searching user does not need to be amember of a group to view human-user-defined results from the group. 17.The apparatus of claim 10, wherein the plurality of human-user-definedrelevancy factors received from the first human user include a timeparameter, and wherein the computer system calculates a momentumquotient based upon the algorithms defined by the first group of humanusers, wherein the first human user's input topics and relevantparameters, resulting in ratings and scorings based upon the relevantparameters that are compared and contrasted to weighted parameters fromother human usergroups, and a set of resulting cumulative summaries,through a user-defined algorithm, are displayed as a momentum quotientand dynamically link to the communications network.
 18. The apparatus ofclaim 10, wherein the computer system facilitates statistical modelingto analyze historical trends, to determine and predict future trends,and to define and determine a momentum quotient of a topic, product orother subject from the priorities, weighting, and perspectives ofdefined associations or user groups, and the data are tracked andvisually displayed by inputting human-user-defined parameters, topicsand the weightings by specifying human-user-defined criteria wherein amomentum quotient can be calculated and quantified, and wherein the userselects parameters that are isolated or correlated for search, trendingand prediction.
 19. The apparatus of claim 10, wherein human usersassociate with other human users, excluding users with similar profileinformation, facilitating searching and incorporating asocial-interaction component, analyze interpersonal compatibility andprovide the ability to contact one or more human users through theapparatus.
 20. The apparatus of claim 10, wherein the apparatus includesa social networking component; wherein social networking aspects arefacilitated and managed by the apparatus.
 21. The apparatus of claim 10,wherein the computer includes notification options that have beenpredefined by a user, administrator and a user group.
 22. Acomputer-implemented method for analyzing, for relevance to a firsthuman-user, source data indexed by the plurality of search-engine-resultpointers, the method comprising: providing a computer servercommunicatively coupled to clients over a communications network;eliciting and receiving into the computer system, which includes acomputer server, from the first human user, a plurality ofhuman-user-defined search terms; eliciting and receiving into thecomputer server, from the first human user, a specification of a firstgroup, wherein the first group is a self-identified set of human users,and wherein the first human user need not be a member of the specifiedfirst group, wherein the RACE program associates a first set ofgroup-relevancy factors with the group; eliciting and receiving into thecomputer server, from the first human user, a plurality ofhuman-user-defined relevancy factors, wherein the plurality of relevancyfactors received from the first human user includes factors that are tobe weighted by the RACE program to rank search-engine results forpresentation to the first human user in addition to the search termsreceived from the first human user; including human-user-definedrelevancy factors from users who have elected to be included in thecomputer system social-interaction component, wherein a user canidentify other users based upon criteria defined by the user, andanalyzing the source data in the computer server for relevance to thefirst human user, at least in part based on weights determined by thereceived plurality of the first human-user-defined relevancy factors andthe first set of group-relevancy factors; presenting, by the computerserver, the analyzed results to the first human user.
 23. An apparatuscomprising: a computer system comprising, a computer server, wherein thecomputer server is communicatively coupled to a plurality of clientsover a wireless communications network, and wherein the computer serverincludes: a relevancy-and-comparison engine (RACE) program stored on theserver that, when the RACE program is executed, analyzes, for relevanceto a first human-user, source data indexed by the plurality ofsearch-engine-result pointers, wherein the RACE program: a source of aplurality of search-engine-result pointers; elicits and receives, fromthe first human-user, a plurality of human-user-defined search terms;elicits and receives, from the first human user, a specification of afirst group, wherein the first group is a self-identified set of humanusers, and wherein the first human user need not be a member of thespecified first group, wherein the RACE program associates a first setof group-relevancy factors with the group; elicits and receives, fromthe first human user, a plurality of human-user-defined relevancyfactors, wherein the plurality of human-user-defined relevancy factorsreceived from the first human user includes factors that are to beweighted by the RACE program to rank search-engine results forpresentation to the first human user in addition to the search termsreceived from the first human user; and wherein the RACE program'sanalysis is at least partially based on weights determined by thereceived plurality of the first human-user-defined relevancy factors andthe first set of group-relevancy factors; wherein the computer systemincludes a mobile electronic device, and includes a dynamically linkedresult to include at least one of the group consisting of a symbol, agraph, and a figure, for ready access via a computer or a mobile device.24. An apparatus comprising: a computer system that comprises a computerserver communicatively coupled to clients over a wireless communicationsnetwork, and wherein the server includes a system forum: arelevancy-and-comparison engine (RACE) program stored on the serverthat, when the RACE program is executed, analyzes, for relevance to afirst human-user, source data indexed by the plurality ofsearch-engine-results, wherein the RACE program: elicits and receives,from the first human user, a plurality of human-user-defined searchterms; elicits and receives, from the first human user, a specificationof a first group, wherein the first group is a self-identified set ofhuman users, and wherein the first human user need not be a member ofthe specified first group, wherein the RACE program associates a firstset of group-relevancy factors with the group; elicits and receives,from the first human user, a plurality of human-user-defined relevancyfactors, wherein the plurality of relevancy factors received from thefirst human user includes factors that are to be weighted by the RACEprogram to rank search-engine results for presentation to the firsthuman user in addition to the search terms received from the first humanuser; and wherein the RACE program's analysis is at least in part basedon weights determined by the received plurality of the firsthuman-user-defined relevancy factors and the first set ofgroup-relevancy factors; wherein the computer system elicits andreceives human-user-defined relevancy factors from users who haveelected to be included in the system forum and social-interactioncomponent wherein a user identifies other human users based uponcriteria defined by the human user, to communicate and solicit feedbackfrom other human users directly via a forum provided by the systemcreating a social interface between human users based upon criteriadefined by the human users themselves.